Magic Quadrant untuk Business Intellegence dan Platform Analytic

Magic Quadrant for Business Intelligence and Analytics Platforms

5 February 2013 ID:G00239854
Analyst(s): Kurt Schlegel, Rita L. Sallam, Daniel Yuen, Joao Tapadinhas


The dominant theme of the market in 2012 was that data discovery became a mainstream BI and analytic architecture. The market also saw increased activity in real time, content and predictive analytics.

Market Definition/Description

This document was revised on 13 February 2013. The document you are viewing is the corrected version. For more information, see the Corrections page on
Gartner changed the name of this Magic Quadrant from "Business Intelligence Platforms" to "Business Intelligence and Analytics Platforms" to emphasize the growing importance of analysis capabilities to the information systems that organizations are now building. Gartner defines the business intelligence (BI) and analytics platform market as a software platform that delivers 15 capabilities across three categories: integration, information delivery and analysis.


  • BI infrastructure: All tools in the platform use the same security, metadata, administration, portal integration, object model and query engine, and should share the same look and feel.
  • Metadata management: Tools should leverage the same metadata, and the tools should provide a robust way to search, capture, store, reuse and publish metadata objects, such as dimensions, hierarchies, measures, performance metrics and report layout objects.
  • Development tools: The platform should provide a set of programmatic and visual tools, coupled with a software developer's kit for creating analytic applications, integrating them into a business process, and/or embedding them in another application.
  • Collaboration: Enables users to share and discuss information and analytic content, and/or to manage hierarchies and metrics via discussion threads, chat and annotations.

Information Delivery

  • Reporting: Provides the ability to create formatted and interactive reports, with or without parameters, with highly scalable distribution and scheduling capabilities.
  • Dashboards: Includes the ability to publish Web-based or mobile reports with intuitive interactive displays that indicate the state of a performance metric compared with a goal or target value. Increasingly, dashboards are used to disseminate real-time data from operational applications, or in conjunction with a complex-event processing engine.
  • Ad hoc query: Enables users to ask their own questions of the data, without relying on IT to create a report. In particular, the tools must have a robust semantic layer to enable users to navigate available data sources.
  • Microsoft Office integration: Sometimes, Microsoft Office (particularly Excel) acts as the reporting or analytics client. In these cases, it is vital that the tool provides integration with Microsoft Office, including support for document and presentation formats, formulas, data "refreshes" and pivot tables. Advanced integration includes cell locking and write-back.
  • Search-based BI: Applies a search index to structured and unstructured data sources and maps them into a classification structure of dimensions and measures that users can easily navigate and explore using a search interface.
  • Mobile BI: Enables organizations to deliver analytic content to mobile devices in a publishing and/or interactive mode, and takes advantage of the mobile client's location awareness.


  • Online analytical processing (OLAP): Enables users to analyze data with fast query and calculation performance, enabling a style of analysis known as "slicing and dicing." Users are able to navigate multidimensional drill paths. They also have the ability to write back values to a proprietary database for planning and "what if" modeling purposes. This capability could span a variety of data architectures (such as relational or multidimensional) and storage architectures (such as disk-based or in-memory).
  • Interactive visualization: Gives users the ability to display numerous aspects of the data more efficiently by using interactive pictures and charts, instead of rows and columns.
  • Predictive modeling and data mining: Enables organizations to classify categorical variables, and to estimate continuous variables using mathematical algorithms.
  • Scorecards: These take the metrics displayed in a dashboard a step further by applying them to a strategy map that aligns key performance indicators (KPIs) with a strategic objective.
  • Prescriptive modeling, simulation and optimization: Supports decision making by enabling organizations to select the correct value of a variable based on a set of constraints for deterministic processes, and by modeling outcomes for stochastic processes.
These capabilities enable organizations to build precise systems of classification and measurement to support decision making and improve performance. BI and analytic platforms enable companies to measure and improve the metrics that matter most to their businesses, such as sales, profits, costs, quality defects, safety incidents, customer satisfaction, on-time delivery and so on. BI and analytic platforms also enable organizations to classify the dimensions of their businesses — such as their customers, products and employees — with more granular precision. With these capabilities, marketers can better understand which customers are most likely to churn. HR managers can better understand which attributes to look for when recruiting top performers. Supply chain managers can better understand which inventory allocation levels will keep costs low without increasing out-of-stock incidents.
The BI and analytics platforms market is broad, covering many different use cases and levels of maturity that span four distinct phases: descriptive, diagnostic, predictive and prescriptive analytics.
The vast majority of applications built with BI and analytics platforms to date could be labeled "descriptive" because critical capabilities, such as reports and dashboards, are used to describe the dimensions and measures of a particular aspect of the business. So, for example, a measure such as on-time delivery could be defined in a well-governed data model and enable users to report on the goal and actual value for that measure by various dimensions, such as customer segments or time periods.
Increasingly, Gartner sees more organizations building diagnostic analytics that leverage critical capabilities, such as interactive visualization, to enable users to drill more easily into the data to discover new insights. For example, visual patterns uncovered in the data might expose an inconsistent supply chain process that is the root cause of an organization's ability to consistently reach its goal for on-time delivery.
As organizations mature at diagnostic analysis, they become so adept at understanding the root causes in their business processes that they can identify the explanatory variables that predict what the measure will be in a future period. For example, a predictive analytic system could be built to forecast the on-time delivery measure. Solutions can be further evolved to prescriptive analytics as the insights from predictive models are integrated into business processes to take corrective or optimal actions.
Right now, most of the user activity in the BI and analytics platform market is from organizations that are trying to mature from descriptive to diagnostic analytics. The vendors in the market have overwhelmingly concentrated on meeting this user demand. If there were a single market theme in 2012, it would be that data discovery became a mainstream architecture (see "More Choices and Complexity in Selecting Data Discovery Tools" for a description of the data discovery architecture). For years, data discovery vendors — such as QlikTech, Salient Management Company, Tableau Software and Tibco Spotfire — received more positive feedback than vendors offering OLAP cube and semantic-layer-based architectures. In 2012, the market responded:
  • MicroStrategy significantly improved Visual Insight.
  • SAP launched Visual Intelligence.
  • SAS launched Visual Analytics.
  • Microsoft bolstered PowerPivot with Power View.
  • IBM launched Cognos Insight.
  • Oracle acquired Endeca.
  • Actuate acquired Quiterian.
This emphasis on data discovery from most of the leaders in the market — which are now promoting tools with business-user-friendly data integration, coupled with embedded storage and computing layers (typically in-memory/columnar) and unfettered drilling — accelerates the trend toward decentralization and user empowerment of BI and analytics, and greatly enables organizations' ability to perform diagnostic analytics.

Magic Quadrant

Figure 1. Magic Quadrant for Business Intelligence and Analytics Platforms
Figure 1.Magic Quadrant for Business Intelligence and Analytics Platforms
Source: Gartner (February 2013)

Vendor Strengths and Cautions


  • In 2012, Actuate continued to post double-digit license growth fueled by its BIRT (Business Intelligence and Reporting Tools) and Xenos product lines. Actuate continues to deepen and broaden its BI application development platform, ActuateOne, to include the support and storage of unstructured data sources, including high-volume print output and PDF archives via X2BIRT, the support of big data insight on touch devices, and additional scorecard and collaboration options for dashboards in BIRT 360. Plus, Actuate now has in-memory processing and the capability to capture and visualize massive datasets through the acquisition of Quiterian, a predictive analytics and visual data mining player.
  • The acquisition of Quiterian brings Actuate a strong set of functionality and algorithms for data discovery, and a new hybrid data store, which combine analytic columnar and in-memory technology that is big-data-friendly. For years, Actuate, with its e.Report and open-source-powered BIRT offerings, was viewed as a dashboard and reporting-only vendor for information delivery that was unable to break into the analysis category of the BI and analytics platform market. Actuate's investment in Quiterian — now BIRT Analytics — will reduce this limitation.
  • Companies choose Actuate products for ease of use for developers, performance, and the ability to support a large number of concurrent users. The products are often used to develop information-based applications for internal and external constituents. In fact, support for large numbers of concurrent users was a leading buying motivation for Actuate customers — rated No. 2 among all vendors in this survey. Also, when references were asked what percentage of employees were users, Actuate references averaged 68.62%, which is significantly higher than the industry average of 30.1%. For performance only, 4.44% of Actuate references indicated that performance was an issue, compared with the industry average of 11.5%. When asked about the most important reasons for buying the software, 28.89% of Actuate references said performance, compared with the industry average of 16.5%.
  • When complex reporting and development requirements are paramount, Actuate products stack up well against competitors. Reference accounts rated Actuate as the No. 2 vendor overall for this requirement. Overall product quality also was rated above average in this year's survey. Actuate reports that more than 25% of its business originates from software vendor OEMs, which, by rule, are not surveyed for the Magic Quadrant. However, this does attest to Actuate's ability to address complex integration requirements for those vendors.
  • Companies choose Quiterian primarily based on the capabilities of simple to complex ad hoc analysis, interactive exploration of data, data mining and predictive analytics, complementing Actuate's traditional core strengths. Quiterian also adds extraction, transformation and loading (ETL) components to Actuate's portfolio, and the road map for Quiterian is to integrate with the ActuateOne product line and provide the capabilities in visual data mining and analytics within Actuate's BIRT iHub. Quiterian also expands Actuate's global representation into Russia, Spain and South America, and adds many new distributors across Europe and Asia.
  • Licensing cost remains a concern. When references were asked what limits wider deployment, 37.78% indicated the cost of the software, compared with the industry average of 25.4% across all vendor references.
  • When compared with Actuate, Quiterian has some concerns, including cost, ease of use for business users, ease of use for developers, support quality and product quality, all ranked below the survey average. The data volume and user size of Quiterian references are in the lowest quartile, either bottom or near bottom, of all vendors in the survey. Actuate needs to inject adequate investment and resources to resolve these issues in time to maintain its sales momentum.
  • Actuate's customers report using a narrower range of functionality than for other vendors — one of the lowest in this year's vendor analysis, and an indicator of its reporting-centric heritage. For example, only 9.8% of Actuate users are power users/business analysts, according to the reference survey, compared with the industry average of 18.1% of users being power users across all vendors. Only 17.05% of Actuate users perform interactive exploration and analysis of data, compared with the industry average of 26.41%. The addition of BIRT Analytics will improve the Actuate analytical portfolio. However, history shows that it requires a lot of management attention — and sometimes years to complete the integration of technologies, processes, organization, sales and marketing — before customers can enjoy the benefits.


  • Arcplan's unified platform incorporates guided analytics, along with budgeting, planning and forecasting capabilities, as well as integrated search and collaboration functionalities. The breadth of this vendor's platform differentiates it from other pure-play BI vendors in this Magic Quadrant that lack an integrated planning capability.
  • The product integrates well as a front end for SAP NetWeaver Business Warehouse (BW), IBM Cognos TM1 and Oracle Essbase, leveraging the information on those systems with the objective of offering capabilities not made available by the megavendors, and at a lower total cost of ownership (TCO). Positioned as a complementary front end for information delivery, arcplan also supports systems such as Microsoft SQL Server, SQL Server Analysis Services (SSAS), Teradata and Kognitio, among others.
  • Arcplan shows a solid list of references, including many global organizations and, in some cases, large deployments. The average number of users for the customers surveyed was 1,087 for a global average for all vendors of 1,249. Although slightly below the industry average, it shows a solid track record in the market.
  • The top reasons why customers select arcplan are functionality, data access and integration, and implementation cost and effort. Additionally, references indicate that the ability to design complex reports is a major contributing factor in selecting this vendor, along with the availability of skills provided by an extensive partner network that includes relevant names such as Deloitte Consulting and Ernst & Young. Customers indicate OLAP and scorecard functionality as being above average.
  • Recent platform improvements include mobile BI with native applications for Apple iOS and Google Android, self-service analytics with an ad hoc interface for information exploration, and arcplan Engage for collaborative BI capabilities.
  • Arcplan has shared some early insights on its next major release that will see a major user interface redesign, simplified administration and improved product interoperability. The new product should help resolve some of the outstanding issues described below in the Cautions section.
  • Arcplan is considered the BI standard by only one-third of its survey respondents — a value in the bottom quartile that positions arcplan as a niche solution for most customers, who are most likely using it in the financial planning area. A substantial part of arcplan's business is linked to SAP — 52% of references indicate that it is their ERP standard — and sales and marketing efforts from SAP for BusinessObjects products and the Hana platform must be considered competitive threats to arcplan's near-term and midterm sales prospects. Interestingly, Hana may also act as an accelerator to arcplan's growth as another source of data for arcplan to analyze.
  • Examining the user profiles of arcplan, we see that the product has the highest percentage of the basic information consumer role of any vendor in the Magic Quadrant. Conversely, the percentage of sophisticated roles (such as power users, business user authors, analysts or data miners) is the lowest. The trend is confirmed by the product usage reported by respondents, which shows some of the lowest ratings for personalized dashboards, ad hoc analysis, interactive exploration and data analysis. These findings highlight the product's focus on simpler descriptive analytics use cases — the lower end of the analytics continuum — and partially explains arcplan's position in this year's Magic Quadrant, which has an increased focus on more advanced analytics capabilities. The company needs to deliver an enhanced information exploration experience and analytics capabilities that appeal to business users, or it will gradually lose competitiveness in the market.
  • Overall, reference customers scored arcplan's product capability below the average of all vendors in this survey. Ad hoc query, development tools and Microsoft integration were noted as particular weaknesses. Customers reported relatively small data volumes (less than 350GB of data on average), and performance concerns were noted with the software — specifically, the inability to handle required data volumes, as well as overall system performance. It is important to note that arcplan sits on top of existing data sources (for example, SAP BW) that may have performance constraints of their own, making it less clear where performance concerns lie.
  • Scores for product quality, customer experience and platform integration were below the average for all respondents, contributing to less positive execution scores in the Magic Quadrant results. Arcplan should put a specific plan in place to address concerns over products and customer experience, or risk losing long-term customer loyalty.


  • In the past year, Alteryx transitioned itself from a more narrowly scoped platform focused primarily on developing geographic-based analytic applications (such as store locations for retailers) to a more broadly scoped platform that can be applied to a broader array of analytic applications, such a pricing optimization and marketing mix allocation.
  • The Alteryx platform provides a strong data integration foundation that enables significant external content integration from vendors such as Experian, D&B, TomTom and the U.S. Census Bureau to enrich business decision making. Moreover, Alteryx provides robust advanced analytic capabilities through integration with R and various prebuilt tools for predictive analytics. In the Magic Quadrant customer reference survey, Alteryx ranked second highest among all vendors when customers were asked about the extent to which they used the platform to perform complex analysis.
  • A growing network of partners develops its own applications using the Alteryx platform for specific industry segments. Its cloud-based architecture enables easy integration with numerous value-added reseller and OEM partners, including Acxiom, Experian and SymphonyIRI Group. Moreover, Alteryx is increasingly being leveraged by management consultants such as Deloitte, Kurt Salmon and BCG to be used in their solution delivery. In 2012, Alteryx also established relationships with more technology partners, such as Teradata, 10gen, Cloudera, Tableau, Hortonworks and Kognitio.
  • From a product perspective, customers rated Alteryx above average in the following capabilities: ad hoc query, development, integrated BI infrastructure, Microsoft Office integration, metadata management, search-based data discovery, predictive modeling and mobile BI. Reference customers also rated the company well on ease of use. When compared with other vendors, Alteryx scored significantly above average in the time to create a new report. Respondents also indicated that they selected the product for its support of large data sources, and for its performance against those large datasets.
  • For a small vendor, Alteryx has a number of significant, high-profile customers using its platform to build strategic analytic applications for various business processes — particularly in the retail sector. In the customer survey, Alteryx responders indicated that they had among the highest number of employees, compared with other vendors, so Alteryx is being used by very large organizations.
  • Alteryx is deployed very narrowly within its reference clients, typically operating within a single department or functional area with few multinational or global references. In fact, it ranked among the lowest of the 38 vendors surveyed for this question. While the analytic applications are often used strategically by the organization, typically only a handful of business analysts use Alteryx. The vendor was also below average on the percentage of respondents that view Alteryx as their standard platform. When customer references were asked about problems with the software, Alteryx did very well on virtually all categories except one. When asked if inability to support large numbers of users was a problem with the software, more than 9% of Alteryx customers indicated it was a problem, compared with the average across all vendors of just 2.5%.
  • Dovetailing with this concern, Alteryx ranked significantly below average, compared with other vendors, in the overall number of users. When customer references were asked if there were any specific barriers to wider adoption, more than 50% of Alteryx references cited the high cost of the software. This is likely due to Alteryx's niche as a platform for doing sophisticated analysis by advanced power users. In 2012, Alteryx introduced a new pricing model that will accommodate more information consumers. Alteryx also expanded its focus to more types of analytic applications, and expanded its efforts to appeal to information consumers leveraging its new Analytics Gallery. The Alteryx Analytics Gallery provides a cloud analytics service whereby organizations can facilitate the consumption of analytic applications that have already been created. However, these efforts to appeal to information consumers have only just begun.
  • Given Alteryx's analytic strengths, customers still have some product concerns beyond price. They are unhappy with the product's data visualization capabilities, and rated it in the lowest quartile of vendors included in this year's Magic Quadrant. However, an increasing number of Alteryx customers are using its analytic capabilities in combination with tools such as Tableau to enhance the visualization output. Customers also note concerns about ease of use for developers and users. As mentioned above, Alteryx is positioning the Analytics Gallery and cloud-based delivery model for easier consumption to drive adoption. That said, Gartner feels that Alteryx needs to continue improving its ease of use for design and consumption for users. Furthermore, Alteryx scored below average on breadth of functionality. Therefore, increasing ease of use and breadth of functionality remain key challenges that Alteryx must overcome in 2013.


  • Birst (and GoodData) are the first cloud-based BI vendors to have enough market traction and customer references to enter the Magic Quadrant. Birst has achieved this momentum — resulting in its placement in the Challengers quadrant — not because of its cloud BI credentials, but rather despite them, given its relatively low cloud BI investment intentions (only around 33% of survey respondents expressing an interest in deploying BI in the cloud). Birst has been successfully competing for and winning deals because of its functional breadth, depth and strength, ease of use and low cost of ownership value proposition. Birst offers a broad and highly rated and integrated set of model-centric, enterprise BI and managed business-user-oriented data discovery capabilities and predictive analytics applications that can be deployed in the cloud or in an on-premises appliance for companies that want to take advantage of Birst's product functionality, but are unwilling to put their BI deployments in the cloud.
  • Survey data suggests that Birst is the "new darling" of the Magic Quadrant (like Tableau Software and QlikTech before it). Its customers rated Birst No. 1 in product functionality and customer (that is, product quality, no problems with software, support) and sales experience, with the near-highest or highest scores across all 14 functional areas, performance and ease of use.
  • Although Birst is a relatively new cloud-based vendor, the platform functionality encompasses all 15 functional areas evaluated in the Magic Quadrant process. Moreover, despite targeting midsize enterprises and departments, the product offers a range of enterprise information management and governance features with integrated data connectivity for a broad range of enterprise applications, data warehouse model autogeneration, and autometadata creation for building a unified semantic layer modeled on top of Birst's relational OLAP (ROLAP) engine and in-memory columnar database (or range of third-party databases, including Oracle, SQL Server, ParAccel, Infobright and so on). Birst's short-term plans include enhancing its enterprise features with version control, data lineage and impact analysis. This end-to-end approach simplifies data management, reduces the time to deployment and offers robust data management capabilities for organizations that need it, or users can connect directly or federate queries to an existing data warehouse or Multidimensional Expressions (MDX) data source.
  • Birst's single front-end user interface for report, ad hoc, dashboard creation, interactive analysis and data discovery is a particularly attractive feature of the platform because it encourages broad use of functionality. Birst customers report among the highest breadth of use of the platform's functionality of any vendor participating in the Magic Quadrant survey. In particular, Birst customers report among the highest percentage of use of static and parameterized reporting, dashboard and interactive visualization functionality of any vendor in the survey. Business user flexibility with IT control is another impressive feature of the Birst platform. Birst provides IT-managed business user data mashup capabilities that enable business users to model their own data (without writing code) in a managed IT sandbox environment sitting on top of the enterprise systems of record repository. Moreover, a number of Birst's customers, particularly in sales and marketing departments, also use its predictive and prescriptive analytic application functionality, which is focused on customer segmentation and scoring, cross-sell/upsell, attribution analysis and targeting, and was developed early in Birst's company history.
  • Functionality, ease of use for end users, and license cost and overall TCO are the top reasons why customers choose Birst. At the same time, Birst customers give it among the top 10 scores of all vendors for ease of use for end users and ease of use for developers, with among the fastest report development turnaround times across all levels of report complexity. Similarly, customers appear to be very happy with Birst's value proposition, ranking it No. 2 of any vendor on the survey for achievement of business benefits.
  • Until now, Birst's focus has been on enterprise application and structured data. It recently added support for constructing map-reduce queries, and for rapidly autogenerating data marts in front of Hadoop, where companies combine and analyze structured and unstructured data from Hadoop.
  • Birst's growth will be hampered by continued IT apprehension to adopt BI in the cloud as it tries to expand beyond departments and small or midsize businesses (SMBs) to large, centrally managed enterprise BI. Cloud adoption in the BI and analytics market is still in its infancy, with the greatest adoption and interest by line of business as opposed to IT. Birst has responded to this challenge by also offering an on-premises appliance, and by competing based on functionality, not solely as a cloud vendor. However, this buying attitude will continue to be Birst's biggest challenge until the market hits a tipping point, which we expect to happen over the next two years.
  • Birst is a venture-funded startup that has limited market penetration beyond North America.
  • While Birst has strong scores in mobile functionality, and close to 80% of its customers report having deployed, piloted or planning to deploy mobile BI in the next 12 months, Birst's mobile device support is limited to native iPad capabilities; however, it has plans to deliver HTML5-based dashboards, thereby enabling dissemination of content to a broader set of devices in the future.
  • Birst's partnering strategy is a work in process, but the company is investing heavily in partner development across key verticals, domains and application expertise — and to expand its global presence, which is strategic to the company's long-term growth plans. Birst courts SAP BusinessObjects and QlikTech partners, as well as regional boutique implementation partners. It is also targeting the reporting OEM market, which currently comprises 40% of business — a space that LogiXML and open-source vendors Pentaho and Jaspersoft are also aggressively pursuing.


  • Founded in 2000 in Mexico, Bitam is a BI and corporate performance management (CPM) vendor headquartered in Reston, Virginia. The vast majority of its business is sold in Latin America, and it has an emerging presence in Western Europe (particularly Spain), North America and Asia.
  • Customers choose Bitam for its ease of use for end users, its product quality and its low cost — license, implementation and overall BI platform ownership costs were ranked in the bottom quartile (among the lowest) of all Magic Quadrant vendors evaluated. In fact, Bitam was ranked top in the aggregated software product quality score, and ranked in the top quartile among vendor references citing no limitations to wider deployment.
  • The Bitam platform offers software components that address core BI, strategic planning and financial planning capabilities, all fielded in a unified platform. The latest version, G7, offers support to multiple devices (which include iPhone, iPad, BlackBerry, Android and gadgets for Windows 7) and includes a new product, Enterprise Forms Server, for design and distribution of business forms.
  • Bitam introduced a software as a service (SaaS) option in 2008 — KPI Online. It is targeted at SMBs and consists of predefined financial and customer applications, as well as CPM functionality and a development platform to create custom BI applications. Customers pay for the service on a monthly basis based on number of applications, users and the amount of data stored in the system.
  • Bitam references scored the vendor above average across all 15 BI and analytic platform capabilities. In particular, Bitam scored well-above average for scorecards, predictive modeling and data mining, and Microsoft Office integration.
  • Bitam's roots in Mexico and other countries in Latin America serve it well in those markets and across the Spanish-speaking world, but it has virtually no brand recognition in other regions. Although Bitam has customers in many parts of the world, it rarely comes up as a contender on shortlists outside its home regions.
  • Like many emerging vendors, references report that Bitam is used for relatively small sets of data by smaller groups of users, compared with other vendors' customers. Bitam's references averaged 501GB, compared with the industry average of 2,918GB. Bitam averaged 265 users, compared with the industry average of 1,249. This indicates that its customers are mostly SMBs or regional/national divisions of multinational corporations.
  • Bitam also ranked below average (29.73%) in the percentage of references offering an analytic application externally to customers, partners or suppliers, compared with the industry average of 36.7%.

Board International

  • Board's main strength remains its offering of a well-integrated BI platform that combines planning, reporting and analysis capabilities in a single product, making the company one of the few also included in the "Magic Quadrant for Corporate Performance Management Suites."
  • Historically, the company has focused on developing and deploying custom analytic applications (on the same foundation as its CPM applications). This unified approach remains its key value proposition, contributing to the responses of 76% of surveyed references that see Board as their standard BI tool (one of the highest scores in this Magic Quadrant).
  • Board's "toolkit" approach to BI application development handles database creation and updates, data presentation and analysis, and process modeling in a single graphical environment without programming. Customers also have praise because the BI platform semantic layer is unified and fully integrated and leveraged across BI platform tools. These are differentiators for the company: More Board customers selected it due to a perceived ease of use for end users and developers, and they report an above-average achievement of business results.
  • Board has an interesting volume of power users, business analyst authors and analysts using the product — only behind Tableau Software and GoodData — and a low percentage of IT authors. This usage profile points to a user-driven BI environment in which the need for IT's involvement is lower than with most other vendors. Surveyed customers' feedback is also positive in terms of product functionality, with all the capabilities (except mobile BI) above average. Microsoft Office integration, reports, dashboards, OLAP, collaboration and metadata management are even in the top quartile.
  • References cite an SMB and departmental support that is three times higher than average; they also continue to show high usage of formal monitoring scorecards. This confirms Gartner's view that Board has a much higher adoption within the planning and control roles of customers' organizations — where its OLAP capabilities and modeled approach to information usage can shine — than it does in areas where information exploration requires increased flexibility, such as in sales or marketing. Recent large deals with extensive deployments, including outside Board's natural environment, may represent a shift from this finding, and should improve the company's Ability to Execute in forthcoming Magic Quadrants, if confirmed by similar customer gains in 2013.
  • Firms considering Board should talk to references that can vouch for its use when scaling to large numbers of users and large data sizes. Board's deployments are among the smallest of the vendors covered in this Magic Quadrant — with 160 users on average, compared with the survey average of 1,249 users — and handle some of the smallest data volumes. With some larger customers being deployed, we will have the opportunity to assess whether this survey finding may reflect historical buying patterns rather than technical limitations.
  • Board has core capabilities in the CPM space, where it has achieved sustained success. This may be offsetting its ability to embrace strong trends in the BI market that would enhance its product, creating new opportunities or, at least, prevent it from lagging behind competitors in some areas. A late recognition of gaps in the product hurts the company's completeness of vision in this Magic Quadrant — for example, mobile BI is still limited to key capabilities, broader analytics functionality is needed as a complement to Board's sweet spot in simulation and what-if analyses, and semanticless data discovery capabilities aren't available. These pending issues may represent negative data points in forthcoming customer bids. Board has initiatives under way to address these concerns — namely new mobility capabilities, a partnership with a Swiss University to develop predictive analytics capabilities, and better user self-service features through the new fast-track component to appear in early 2013. These are steps in the right direction.
  • Although sales execution remains solid and above market average, Board's core markets are still overly focused in Europe — which represents 83% of the business, with emergent adoption elsewhere. The company is working to improve its presence in the U.S., Latin America and parts of Asia, where it is showing traction that helps to confirm its worldwide expansion.
  • Board's customers have reported below-average product quality in the past, coupled with troubled support and a diminished customer experience. This year's assessment has improved in all these metrics, although remaining below average with regard to support response time. The company must continue to closely monitor and improve the situation to prevent customers' defection, as surveyed references reported higher than average plans to discontinue the product within the next three years.


  • Founded in 2007 and well-funded with 200 employees worldwide, GoodData is one of two new SaaS BI and analytics platform vendors to be added to the 2013 Magic Quadrant. GoodData in particular has also tapped into the emerging data-as-a-service trend. Where most of the semantic-layer-based BI platforms in this market were created to complement a data warehouse, GoodData was created to enable trusted data aggregators to develop a subscription-based offering around a specific set of industry data with the reporting and analytics capability embedded. This is a distinctly different vision than that of most vendors in this Magic Quadrant. The idea is to empower organizations to create their own revenue-generating data-as-a-service offering. This messaging around the monetization of their data is a big reason for GoodData's rapid growth last year. Typically, the buyer is not IT looking for data integration or OLAP capabilities, but rather is a VP-level business executive looking to purchase a solution. These executives are looking to provide a data-as-a-service offering to their clients, partners and suppliers. Sixty-seven percent of GoodData customers have externally facing analytic applications, compared with just 37% for the market average. GoodData saw strong customer adoption in 2012, with revenue increasing fivefold and customers increasing three times compared with a year ago. In 2012, GoodData also grew its "Powered by GoodData" partner program revenue by nearly 500%, and more than doubled the number of partners.
  • While the overall trend toward a data discovery architecture has outshined the cloud-based BI and analytic trend, there are some distinct similarities. In particular, cloud-based BI/analytics and data discovery tend to combine the three major phases of BI and data warehouse architectures (ETL for data integration, database for storage and management, and a presentation layer for reporting and analysis). Instead of going to three separate vendors and, consequently, three different teams for this functionality, GoodData provides its own custom-developed data integration solution: It licenses Vertica for a database and has built its own HTML5-based presentation layer.
  • The other similarity GoodData shares with data discovery architectures is a data mashup — an easy way to combine disparate data to quickly create an analytical view. GoodData extends on this idea and calls it a "Bash," which blends data, people and process in a particular business domain. GoodData also comes with an array of connectors with its data integration tool to Facebook, Twitter,, Omniture and major data sources on the Web. GoodData customers have 39% of data coming from external sources, compared with a market average of 23%. Being able to mash up these external data sources with internal data is an increasing trend to improve the value of existing reports and dashboards, which tend to have an insular view, being sourced typically from internal sources.
  • While GoodData customers have fewer end users than the market average, GoodData still has a respectably high number of users (832 on average) for being a small and relatively new vendor. Also, 43.59% of these users are external to the client's organization, which is significantly above average. Moreover, GoodData scored particularly high among its customers, averaging 84.7% of employees using GoodData, compared with the market average of just 30% of employees using the platform. GoodData customers also rated its reporting, dashboards, scorecards and interactive visualization capabilities as above average. Another trend helping to drive user adoption is mobility. Based on the reference survey, 21% of GoodData users are actively using mobility.
  • In the reference survey, GoodData customers indicated a lack of ease of use for developers, and an overall lack of governance and data quality were the primary limitations to wider deployment. GoodData launched CloudConnect in 4Q12 to address data quality issues and create a more developer-friendly interface to the platform. Based on the customer reference survey, GoodData customers average just 137GB, compared with the industry average of 2,918GB. On the positive side, GoodData customers spent slightly less time developing reports than the market average. Also, customers rated the migration experience to be extremely straightforward, which is to be expected, given the SaaS model.
  • While GoodData customers ranked the sales and pricing experience positively, the same was not true for their rating of GoodData's overall product capabilities. Customers rated GoodData below average for 10 capabilities, including ad hoc query, development tools, BI infrastructure, OLAP, Microsoft Office integration, collaboration, search-based data discovery, prescriptive modeling simulation and optimization, predictive modeling and data mining, and mobile BI.
  • Despite its promising OEM and reseller partner relationships, GoodData lacks a significant direct sales channel, and with offices in just the U.S. and the Czech Republic, it is particularly weak in providing a global support infrastructure. Beyond the global support, GoodData also lacks a strong vertical strategy, and has no focused effort to meet the particular needs of a vertical industry.


  • IBM continues to maintain its leading position on the Completeness of Vision axis for this year's Magic Quadrant, as it scores very well on virtually all the vision criteria. In particular, IBM's overall marketing strategy strengthens the messaging of its core BI (Cognos) and predictive analytics (SPSS) acquisitions. This is not typical with most megavendor acquisitions. Also, customer feedback has improved, largely due to the continuous customer migration to IBM Cognos Business Intelligence 10.x from Cognos 8 Business Intelligence.
  • IBM further expanded its BI and analytics offerings in 2012 through build — for example, IBM Cognos BI 10.2, Cognos Insight, SPSS Modeler 15, Analytical Decision Management 7.0 and Analytic Answers — and through acquisition — for example, Tealeaf Technology, Varicent Software and Vivisimo. Cognos Insight is a personal analytics product that can be deployed stand-alone on the desktop, or as an analysis and planning client as part of the Cognos server-based products. Analytical Decision Management enables organizations to automate, optimize and govern repeatable business decisions. The business analytics portfolio was enhanced by the acquisition of Varicent, a leading provider of analytics software for compensation and sales performance management.
  • IBM improved its ability to address departmental, workgroup or smaller company business analytics requirements through the release of IBM Cognos Express 10.1, which provided comprehensive BI suite functionality along with budgeting, planning and forecasting capabilities at a lower license cost, but with a limitation of up to 100 end-user seats.
  • Analytic Answers was another significant offering added recently. Gartner has predicted that, by 2014, up to 40% of analytics projects will be service-led and software-supported. IBM, delivering "analytics as a service," will enable organizations to mitigate one of the most critical nontechnical barriers to advanced analytics adoption: the lack of analytical skills. Analytic Answers is not simply a cloud offering that enables a shorter time to market, or turns capital expenditure into operating expenditure to encourage business analytics adoption. Rather, it is an analytics platform with prebuilt, domain-specific data models and embedded, relevant, statistical and advanced analytical algorithms that offer answers to industry-specific questions. This offering will enable IBM to effectively leverage its complete analytical assets — including analytical software, hardware, analytical knowledge, industrial practices, intellectual property and cloud delivery model — to allow maximum user access to IBM advanced analytics capabilities.
  • According to this year's customer reference survey, nearly 60% of references are using Cognos BI 10.x, which is three times more than Cognos 8 BI. Also, more than 80% of 10.x references claimed Cognos as their BI standard. Gartner inquiries in 2012 were in line with the reference survey results that customers are, in general, satisfied with Cognos BI 10.x, and with the migration process.
  • From the survey, the top reasons why customers select IBM are road map and future vision, product quality, and ability to integrate with information infrastructure (database, middleware). IBM's road map and future vision scored significantly above average; thus, it is weighted heavily in reference purchasing decisions.
  • Performance remains a concern, although primarily with the Cognos 8 BI base. When asked about problems with software, 24% of IBM references cited poor performance as a concern, compared with the industry average of 11.5% across all vendors. When asked about product-specific limitations to a wider deployment, 16% of references cited poor performance, compared with the industry average of 6.8%. IBM addresses this problem in 10.x by providing further query engine enhancements in 10.2 (in-memory ROLAP, aggregate awareness and so on).
  • References continue to cite the Cognos products as more difficult to use. When asked about the most important reasons for choosing IBM, only 17.74% of references cited ease of use for end users, compared with the industry average of 35.1%, putting IBM in bottom quartile. Also, IBM references cited an average of 6.45 days to create a report, compared with the market average of 3.95 days, again ranking IBM in the bottom quartile. Readers should note that this statistic is a blended average of the time required to develop simple, moderately complex and complex reports. IBM has made usability a priority investment area, and this is reflected in the higher survey ratings for Cognos BI 10 versus Cognos 8 BI.
  • References rated IBM as having slightly lower than average customer experiences, with support and sales interactions, along with product quality, rated in the lower quartile of all vendors reviewed in this research. However, Cognos BI 10 references continued to rate product functionality near the top of all vendors, and support, sales and product quality were rated better than for Cognos 8 BI.
  • In the user activity section of the reference survey, IBM customers were above the average in the percentage of users viewing static reports — 49.67% compared with the industry average of 39%. Also, IBM customers were below average in the percentage of users performing interactive exploration and analysis of data, with 13.46% of IBM references compared with the industry average of 26.41%.

Information Builders

  • Customers choose Information Builders largely for the strength of its data access and integration, its ability to support a large number of users concurrently, and its overall product quality. The company's broad information management capabilities bolster its BI platform and provide differentiation from other pure-play BI competitors. Information Builders' customer references almost doubled the industry average for number of users.
  • When asked about problems with the software, virtually none of Information Builders' customers indicated problems with performance or the ability to support large numbers of users. Information Builders' customers also cited no significant product-specific limitations toward a wider deployment. The only non-product-specific limitations related to an inability to gain user buy-in to an enterprise approach. Nevertheless, almost two-thirds of respondents consider Information Builders to be the enterprise BI standard. Moreover, references indicated that 46.33% of their employees were Information Builders users, compared with the industry average of 30.1%. This statistic underscores Information Builders' focus on more operational BI deployments, which emphasizes delivering information to the point of work.
  • Information Builders' customer references reported strong BI functionality across the BI platform spectrum. The WebFocus customers surveyed rated the company at or above average in 10 out of 14 capabilities. Its strongest area remains reporting. Information Builders' customers predominantly make great use of parameterized reporting (for example, interactivity via prompts, drilling or filters) for consumers and casual users. The percentage of users performing parameterized reporting was 52.19%, compared with the industry average of 41.51%. By and large, this is the sweet spot for Information Builders' WebFocus, particularly when deployed to a large number of external users. Information Builders continues to attract customers that are looking to deploy customer-facing reporting applications.
  • The major change in Information Builders' 2012 marketing messaging was to promote the three pillars of its platform: intelligence, integrity and integration. WebFocus is fully integrated with the firm's iWay integration platform, which provides adapters for multiple data sources, as well as data federation, profiling and quality capabilities, geocoding and real-time search index management, business activity monitoring, complex-event processing, file-based integration and master data management. This integration makes Information Builders a good fit for organizations without a data warehouse, and for operational reporting. In 2012, Information Builders also significantly expanded its array of packaged analytic applications for various vertical and horizontal domains. In particular, Information Builders delivered offerings for the public sector in state and local governments, and in the healthcare provider segment.
  • A key challenge for Information Builders is to address its lack of a data discovery offering. With references citing just 12.59% of users performing interactive exploration and analysis of data, Information Builders scores significantly below the industry average of 26.41% of users across all vendors in the survey. To address this concern, Information Builders has expanded its OEM relationship with Advizor to now include Advizor's complete workbench. Moreover, Information Builders has integrated the Advizor technology within the WebFocus portal to make it more easily accessible in broader BI and analytic deployments. Also, Information Builders has rewritten its charting engine to include new visualizations, which are integrated across the entire platform.
  • Surprisingly, just 5.36% of Information Builders references indicated that they are actively using mobile BI today, compared with the industry average of 11.34%. This statistic from the reference survey is surprising, considering that Gartner's other interactions with Information Builders' clients indicate a strong focus on mobility. Also, Information Builders does not charge for its mobile capability, but rather makes it widely available by supporting HTML5, as opposed to requiring native app support. The WebFocus server has the intelligence to deliver content to any device while taking on native gesturing and menu characteristics. Moreover, according to the reference survey, a higher percentage (40.18%) of Information Builders' references plan to deploy mobile BI, compared with the industry average of just 32.20% across all vendors' references.
  • Only 41.1% of Information Builders references cited that they were running the latest version of the software, compared with the industry average across all vendors of 59.3%. For this particular question, Information Builders ranked 36 out of the 38 vendors included in the survey.


  • Jaspersoft offers a comprehensive, highly embeddable, open-source BI platform. The Jaspersoft Enterprise Edition — latest version 5.0.1 of its platform — includes JasperReports Server (which incorporates a reporting server, ad hoc query [including an enhanced user interface for analysis], in-memory analysis and dashboarding), JasperReports Library, Jaspersoft iReport Designer, Jaspersoft Studio (an Eclipse-based report designer), Jaspersoft OLAP and Jaspersoft ETL, which is the open-source ETL engine from Talend and includes advanced functions from Talend's commercial edition, such as change data capture, monitoring, job versioning and more. The platform also supports full multitenancy for cloud and SaaS deployments.
  • Jaspersoft supports a broad range of native Apache Hadoop and NoSQL connectors. It also has support for iPad and HTML5-based reports, as well as a software development kit for building mobile BI applications on the iOS and Android platforms. In 2012, Jaspersoft released a series of enhancements, including a unified HTML5-based user interface targeted at nontechnical users for delivering ad hoc reporting and a columnar-based, in-memory analytic engine for structured and unstructured data. Additional improvements included interactive reporting, data exploration, data federation, an enhanced metadata layer supporting data lineage in a single report view, enhanced multidimensional analysis support (including Microsoft Analysis Services [in addition to ROLAP-based Mondrian]), programmatic API access for Java and PHP programs, and native direct data access for more than a dozen different big data/NoSQL engines, like Hadoop's Hive and HBase, MongoDB and Cassandra.
  • Some of Jaspersoft's more visionary attributes reflect its unique view of the future BI market; for example, its platform runs natively in the major cloud (platform as a service and infrastructure as a service) environments — such as Amazon Web Services, VMware Cloud Foundry, Red Hat OpenShift and GoGrid — supporting cloud-based development and deployment of BI applications. Jaspersoft is one of the first BI vendors to support emerging cloud-based big data stores, including Google BigQuery and Amazon Redshift. Jaspersoft uniquely provides native access to big data stores (like MongoDB and HBase) that do not have an SQL interface, directly from its reporting and analysis server (without requiring ETL), for applications requiring low latency, direct data exploration and analysis. Like some other vendors, Jaspersoft also provides connectors to Revolution Analytics, the open-source R-based predictive analytics, eXo for collaboration, and connectors to diverse big data sources.
  • Due to its embeddable architecture, and because customers can embed its software without being bound by the GNU General Public License terms and conditions, Jaspersoft earns more than half of its business from more than 600 OEMs and SaaS providers that include Jaspersoft among the BI components in their software offerings, as well as other businesses that integrate Jaspersoft into their internal applications. Jaspersoft also has an established partner network that includes companies such as Red Hat, VMware, IBM, Google, Amazon and Novell. Note that OEMs are not included in our survey results.
  • Cost is a compelling part of the Jaspersoft value proposition, and is a major ingredient driving its success. Customers cite low TCO, license cost, and implementation cost and effort among the top reasons for choosing Jaspersoft as their BI vendor, more often than for most other vendors in the survey. Its low-cost value proposition extends beyond the low initial license cost. Jaspersoft customers also report below-average overall BI platform ownership costs. Its low-cost model also makes it well-suited to extranet deployments in which the number of users is often unknown. Jaspersoft customers use its platform for an above-average percentage of externally facing applications, as well as for cloud-based deployments.
  • Even though Jaspersoft has a fully featured BI platform, it is used narrowly in organizations — mostly for reporting. In fact, static reporting and parameterized reports are the only two user activities that are above the survey average. Because of Jaspersoft's usage profile, the platform remained below average in the complexity of workload scores, and in terms of the breadth of use of its BI platform functionality. This usage is consistent with Jaspersoft's roots as an open-source reporting and embeddable developer tool; its customers are beginning to more widely implement the broader set of BI functionality available as part of the Jaspersoft platform. This is also consistent with anecdotal evidence from Gartner inquiries that suggests that organizations are increasingly using low-cost alternatives, such as open-source and low-cost embeddable products, to offload reporting functionality or implement professional-grade reporting within an internal application to lower overall BI portfolio costs, while using another BI platform as the enterprise standard.
  • Jaspersoft tends to be deployed with smaller data volumes than the survey average. References averaged 1,274GB of data, compared with the industry average of 2,918GB.
  • Jaspersoft is still in the process of distancing itself from its IT-oriented, do-it-yourself open-source project roots. Jaspersoft earned below-average scores for ease of use for end users and developers. Despite these results, Jaspersoft customers still report below-average BI platform ownership costs. Moreover, its customers maintain a positive view of the vendor's future, and report successes with Jaspersoft's product (as defined by expanded usage) over the past year. One explanation for this paradox is that the value organizations derive from Jaspersoft's lower-cost deployments is in line with their level of investment and expectations.


  • In 2012, LogiXML continued to deliver on its value propositions of ease of use, rapid time to deployment, "embeddability" and lower cost, compared with the offerings of the traditional enterprise and open-source market players with which it competes, but with the advantage of generally higher customer satisfaction with the platform's ease of use, product functionality, support, sales experience and product quality. Compared with last year, LogiXML remains about the same on the Completeness of Vision axis; however, better customer feedback has improved its Ability to Execute and pushed LogiXML into the Challengers quadrant for the first time.
  • LogiXML's BI platform is sold as a single platform, which is based on core or CPU with no limitations on user numbers. The platform includes reporting, analysis and dashboards for IT and business users, plus data integration. In 2012, Logi Info v11 included an enhanced visual presentation with interactive functions, such as advanced selection, filtering and association functions. The 2013 road map includes new data visualizations for further improvement of mashup and data discovery capabilities for business users. The latest version of the Logi engine also improves performance on large datasets. With these changes, LogiXML is planning to rebrand the name of the company in the first half of 2013.
  • LogiXML targets SMBs, departments in large enterprises, and software/SaaS companies that embed LogiXML's solutions in their own products and applications. Similar to open-source vendors, a large percentage of LogiXML's customers are independent software vendors (ISVs) or SaaS vendors that incorporate the product because of its embeddability and low cost. Although targeted more at BI developers and IT managers, LogiXML's products include an ad hoc reporting solution for nontechnical business users. Business-user-oriented interactive visualization is an area in which LogiXML continues to improve. LogiXML reported that, in 2012, its growth in customer numbers was close to 30%, of which 80% have more than 500 users. Some implementations, many as part of customer-facing applications, are deployed to more than 500 users — and LogiXML's unlimited user license model makes it economical to do so. Compared with most other vendors in the survey, LogiXML has among the highest percentage of external users using its product for more externally facing applications (43% this year).
  • Cost is one of the primary reasons why customers choose LogiXML. It is chosen more often — in fact, ranked only second to SpagoBI — than most other vendors for overall TCO, license cost, and implementation cost and effort. Although LogiXML tends to focus on reporting and dashboards with less complex deployments in terms of user and data size, global deployment, and breadth and complexity of use than its competitors, it has one of the lowest total costs per user in the survey.
  • Ease of use goes hand-in-hand with cost as a key strength for LogiXML, which is reflected by its customers rating it above average in the survey. The company includes interfaces for business users and IT developers to create reports and dashboards. However, its IT-oriented, rapid development environment seems to be most compelling for its customers. The environment features extensive prebuilt elements for creating content with minimal coding, while its components and engine are highly embeddable, making LogiXML a strong choice for OEMs. The platform productivity features are enhanced by a robust, user-community-driven website (Logi DevNet), which contains a best practice discussion forum and hundreds of sample projects, tutorials and training videos. LogiXML claims that DevNet currently has more than 8,000 members from 130 countries. In addition to ease of use, LogiXML stayed in the top quartile for "BI infrastructure" and "BI development tools," with a top percentage of its customers reporting "no product-related problems for wider deployment." These results confirm LogiXML's strength as an easy to use, high-productivity developer platform.
  • LogiXML is in the cross hairs of competing, low-cost alternatives from open-source vendors and Microsoft. While LogiXML has received a fresh round of funding and achieved strong market momentum over the past three years, it is still small, with more limited resources than other vendors (particularly Microsoft, open-source vendors and other large traditional BI vendors) when it competes for roughly the same types of customers (SMBs and departments, embedded use cases, and OEMs). The survey showed that Microsoft is the major ERP vendor (nearly one-third) and the data warehouse vendor (more than two-thirds) in LogiXML's customer environment. Head-to-head competition with Microsoft is foreseeable as Microsoft is pushing heavily in the BI and analytics platform space, too. LogiXML may find its low-cost advantage becoming less apparent against Microsoft's software stacks.
  • LogiXML's customers tend to have smaller numbers of users and data volumes (less than half and less than one-third of the survey average, respectively), while a less than average number of references consider it to be their BI standard. A key test of LogiXML's market momentum, beyond its current SMB and departmental target market (and its ability to make upward progress in the Magic Quadrant in the future), will be its ability to expand its footprint beyond single or multiple departments, and to become or replace the incumbent enterprise BI standard in a larger percentage of its accounts.
  • LogiXML currently focuses on the SMB and OEM spaces, where pervasive and large enterprise deployments are less common.
  • While LogiXML has an above-average overall product rating, its sweet spot is clearly static and parameterized reporting and dashboards, which are used by the majority of its customers. In fact, 76% of its customers use its Logi Info product (reporting and dashboards), while 13% use its ad hoc product. LogiXML added real-time OLAP capabilities for in-memory analysis in 2011, and interactive visualization and advanced analysis capabilities in 2012. References showed that both capabilities are only slightly over average in the survey.
  • LogiXML's highly embeddable architecture is a positive and a negative. On the one hand, this attribute makes it highly attractive to organizations embedding BI into existing operational applications, and to OEMs looking to embed its product — an area where LogiXML has been successful to date. On the other hand, its high percentage of OEM business will limit its ability to expand brand awareness, as most users (and potential customers of the product) will never know they are using the company's products.
  • Although LogiXML has, over the past year, executed vertically focused marketing campaigns targeted particularly at healthcare, manufacturing and financial services, and although its OEM partners create vertical solutions using its platform, it has more limited, directly marketed, packaged vertical offerings than many leading vendors. Moreover, its geographical presence, while growing outside North America (particularly in Western Europe and Asia, where the company has OEM, reseller and system integration partners), is more limited than for its larger competitors.


  • Microsoft offers a competitive and expanding set of BI and analytics capabilities, packaging and pricing that appeal to Microsoft developers, its independent distributor channel, and now to business users through enhanced BI and data discovery capabilities in Excel 2013. The company's strategy has been to enhance the BI capabilities in three of its core offerings with each release — including Microsoft Office (specifically Excel), Microsoft SQL Server and Microsoft SharePoint — to increase their value and drive upgrades. Moreover, Microsoft hopes to leverage its cloud offering to enhance opportunities to grow its market share and deliver value by lowering cost of ownership and accelerating product enhancements and the adoption of new releases.
  • By incorporating BI capabilities into its most ubiquitous products, and by removing deployment barriers, Microsoft virtually guarantees its BI offering's continued and even expanded adoption, particularly in organizations that have standardized on Microsoft for information management. As a result of this strategy, since the company's serious entry into the market in 2000, Microsoft's BI market share has grown steadily to take the No. 3 spot in 2011. With the new functionality added and planned for Microsoft Excel, we expect Microsoft's market share growth to continue.
  • Microsoft's packaging strategy for BI and enterprise pricing often makes it a compelling license cost value proposition for organizations that want to deploy BI to a wider range of users, or that want to lower overall BI portfolio license costs by using lower-cost BI tools for basic BI functions. As Microsoft continues to enhance its BI capabilities in products that most companies already own and use (Excel, SQL Server and SharePoint), the functionality premium for alternatives may become increasingly difficult for many organizations to justify. In the Magic Quadrant customer survey, more Microsoft customers cite TCO and license cost as the No. 1 reasons for selecting Microsoft as a BI vendor, as opposed to most other vendors in the survey. This has been the case for each of the past six years in which Gartner has run the survey.
  • Nowhere will Microsoft's packaging strategy likely have a greater impact on the BI market than as a result of its recent and planned enhancements to Excel. Finally, with Office 2013, Excel is no longer the former 1997, 64K row-limited, tab-limited spreadsheet. It finally begins to deliver on Microsoft's long-awaited strategic road map and vision to make Excel not only the most widely deployed BI tool, but also the most functional business-user-oriented BI capability for reporting, dashboards and visual-based data discovery analysis. Over the next year, Microsoft plans to introduce a number of high-value and competitive enhancements to Excel, including geospatial and 3D analysis, and self-service ETL with search across internal and external data sources. These enhancements, along with planned support for analyzing large and diverse data (PolyBase, Microsoft's platform to enable a single query across relational and Hadoop data sources, is due in the first half of 2013), contribute to Microsoft's strong product vision score this year — one of six measures used to determine its positive movement in overall vision position.
  • Microsoft Excel users are often disaffected business BI users who are unable to conduct the analysis they want using enterprise, IT-centric tools. Since these users are the typical target users of data discovery tool vendors, Microsoft's aggressive plans to enhance Excel will likely pose an additional competitive threat beyond the mainstreaming and integration of data discovery features as part of the other leading, IT-centric enterprise platforms. With the introduction of Office 2013, these target users will begin to have a compelling reason to use the BI and data discovery capabilities they already have in their beloved Excel. To have a material impact on the market, the challenge for Microsoft will be to reduce product release cycles (Office release cycles have been every two years or more) and condense customer release adoption cycles (most companies deploy one or more versions of Office behind the latest). Microsoft intends to address these significant barriers in 2013 by shortening product update cycles, while leveraging the cloud (Click-to-Run) to deploy the latest releases to users in a timely fashion. The success of this strategy largely depends on user adoption of Microsoft cloud offerings, which should roll out and be sold in full force in 2013.
  • Microsoft's market success is also driven in part by its IT-oriented BI authoring tools within SQL Server, which are based on Visual Studio, the broadly adopted development environment. Microsoft continues to be viewed positively as a development environment with armies of global developers and developer partners skilled in Visual Studio .NET, and because it is building and selling analytic applications and solutions on top of the Microsoft stack. This approach, along with targeted marketing efforts and programs for building strong developer communities and support, has helped Microsoft lower the cost and expand the availability of its BI skills. In the Magic Quadrant survey, Microsoft customers rated its BI platform infrastructure among the highest compared with most other vendors, and a higher percentage of customers use it extensively. Moreover, "wide availability of skills" is among the top reasons why customers select Microsoft more often than all other competing vendors in the survey.
  • OLAP continues to be a widely deployed capability of the Microsoft BI platform, with more than 90% of Microsoft customers reporting they use it. This is among the highest adoption compared with other vendors. This success can be attributed to the packaging of Microsoft SQL Server Analysis Services functionality, its use as an optimization layer in most Microsoft BI deployments, and because of its optimizations with Microsoft front-end tools. Building on the in-memory capabilities of PowerPivot in SQL Server 2012, Microsoft introduced a fully in-memory version of Microsoft Analysis Services cubes, based on the same data structure as PowerPivot, to address the needs of organizations that are turning to newer in-memory OLAP architectures over traditional, multidimensional OLAP architectures to support dynamic and interactive analysis of large datasets. Above-average performance ratings suggest that customers are happy with the in-memory improvements in SQL Server 2012 compared with SQL Server 2008 R2, which ranks below the survey average.
  • While Microsoft's BI platform is attractive to SMBs, it is widely deployed in large enterprises as a standard with among the highest data volumes and user counts. Among the highest percentage of customers say they have standardized on the Microsoft BI platform. In addition, among the highest percentage of survey respondents of any vendor say they choose Microsoft because it is an enterprise standard, and because of the wide availability of skills. Like the other megavendors, stack centricity is evident among Microsoft customers, which use Microsoft Dynamics as their primary ERP two times more frequently than the survey average, and use Microsoft SQL Server as their primary enterprise data warehouse (EDW) almost three times more frequently than the survey average.
  • Microsoft, like the other megavendors, can meet some of the broadest range of functional requirements, and has among the highest RFP mapping scores of any vendor. However, customers using SQL Server 2012 rate the product functionality significantly higher than customers using SQL Server 2008 R2. While all SQL Server 2008 R2 functional scores are below the survey average, SQL Server 2012 metadata management, Office integration, search-based BI, OLAP, BI infrastructure capabilities, development tools, reporting and ad hoc query all received above-average ratings. Microsoft's weighted average product score across both product versions is in the bottom quartile, due to a smaller number of SQL Server 2012 customer respondents. Microsoft also rates among the highest in percentage of users that say absent or weak functionality is among the top problems they have with the software (this is mostly reported by SQL Server 2008 R2 customers). Similarly, product quality, support, performance and sales experience continue to be below average for SQL Server 2008 R2, but SQL Server 2012 customers report above-average experiences across the same measures. While Microsoft's partner-driven sales model drives global growth for the company, Gartner inquiries suggest that this approach often makes it difficult for customers to find their Microsoft sales representative. This frustration may be the source of downward pressure on Microsoft's sales experience scores. The dichotomy of results between SQL Server 2008 R2 and SQL Server 2012 customers affected Microsoft's Ability to Execute position on this Magic Quadrant. As customers upgrade to SQL Server 2012 and Office 2013, we expect to see improved overall product, customer and sales experience results.
  • Multiproduct complexity is a challenge. Because Microsoft's BI platform capabilities exist across three different tools (Office, SQL Server and SharePoint) that also perform non-BI functions, integrating the necessary components and building the applications is left to the organization. Microsoft's do-it-yourself approach puts more of the BI solution's development and integration onus for the platform components on customers, compared with the all-in-one purpose-built BI platforms offered by most other vendors in the BI market. Microsoft is depending on its cloud offerings to reduce the deployment complexity, particularly for smaller companies without the necessary skills. Partners, such as HP, have also stepped in to address this barrier to adoption with packaged offerings, including reference architectures and preloaded, integrated and configured appliances with Microsoft's BI components.
  • Microsoft BI is primarily used for reporting by report consumers, as opposed to a broad spectrum of more advanced types of analysis. Microsoft BI capabilities tend to be used by an above-average percentage of users to total employees, as well as by an above-average percentage of external users, with most users — more than 65% identified as consumers or casual users — primarily using reporting and parameterized reports. Users' complexity of analysis score for Microsoft BI is also below the survey average. We expect this to change with the introduction and adoption of Office 2013, which includes a visual-based data discovery tool, Power View and other interactive analysis capabilities within Excel.
  • Microsoft lags behind most other BI vendors in delivering mobile BI capabilities. It has been slow to deliver BI on mobile devices. Latent demand for Microsoft mobile BI is evident from the survey, with Microsoft customers reporting among the highest percentage of respondents (48%) planning to implement mobile in the next year — second only to Oracle, which has also lagged in delivering mobile capabilities.
  • Microsoft CPM capabilities (for example, planning and budgeting) are limited to embedded functionality, such as financial reporting, in Microsoft Dynamics applications. As a result, Microsoft's performance management product strategy is limited compared with the other stack vendors (IBM, Oracle and SAP), which offer stand-alone CPM products that are also (at least in theory, or on the road map) integrated with the rest of their BI stacks. Microsoft instead relies on its partners, such as Tagetik and Board, to deliver Microsoft-based CPM solutions.
  • Most companies buy Microsoft because of low license cost and overall low cost of ownership. In fact, licensing cost can be favorable because of packaging, for companies with enterprise licensing agreements, and for companies that move to Office 365. However, while Microsoft's total BI platform ownership cost (including license, hardware, implementation and ongoing development) is below average on a per-user basis, it tends to be consistent with other megavendors, mainly due to implementation and ongoing development costs, which compose more than 75% of three-year BI platform ownership costs, particularly in large deployments. There is evidence that the improved ease of use and lower report development times for SQL Server 2012, as well as the integration and upgrade benefits from cloud deployment, may help improve this cost curve for these Microsoft customers.


  • MicroStrategy specializes in enterprise BI deployments running on top of large EDWs. It is typically deployed in larger enterprises that consider it to be their enterprise BI standard. Its deployments remain among the most complex in terms of functionality, large numbers of users, high data volume and wide deployment across an enterprise, although it is not as distinctive from competitors as in the past.
  • The BI platform was built from the ground up through completely organic development. The high level of integration of the individual platform components and the reusability of MicroStrategy's well-architected and object-oriented semantic layer are the result of this strategy. Another consequence is that customers identify product quality (which includes stability, reliability and being bug-free) as one of the top reasons for selecting MicroStrategy.
  • By avoiding the hassle of integrating products from the acquisition of smaller vendors, MicroStrategy is able to spend more development effort in the core BI product, in reinforcing its enterprise-scale pedigree through initiatives for high performance across all layers of its platform, and in providing better administration tools to help manage complex deployments. Moreover, this approach frees the company's resources to have a bold innovation strategy in areas such as mobile, cloud and social.
  • The heavy investment in mobile BI, initially on Research In Motion (RIM) BlackBerry devices and now on the Apple iPhone/iPad and Android devices, is paying off for MicroStrategy. The company is the Magic Quadrant leader in terms of adoption, with close to 50% of the surveyed customers actively using or piloting mobility for BI. In 2012, it was recognized by Gartner as having the broadest and most advanced set of mobile capabilities in the BI market (see "Critical Capabilities for Mobile BI"), and it has continued to evolve the mobile tool, adding new visualizations, improving performance and delivering tight integration with the data discovery tool (Visual Insight) and the cloud offerings. As a result, MicroStrategy is being considered for competitive bids in companies that see mobility as a strategic imperative; in some cases, it is even succeeding to replace or complement long-established BI vendors that lag behind in mobile BI.
  • MicroStrategy has also embraced cloud BI as a strategic differentiator and is delivering a renewed set of solutions. Cloud Personal and Cloud Express (the entry-level and workgroup options) raise awareness in the market, but it is Cloud Platform that may become a game changer for the company. It provides a comprehensive solution by bundling ETL and database solutions with the full stack of MicroStrategy's BI tools and its own system optimization and administration services. This results in the capability to set up a new BI platform environment in a few days — scalability according to demand and potentially lower TCO. MicroStrategy claims to be gaining deals with this solution — including some large companies within and outside the current customer base, making the cloud offering its most successful product in the first year since launch.
  • During 2012, MicroStrategy's data discovery tool, Visual Insight, was updated with new visualization capabilities, improved usability, additional analytic functions and better integration with the enterprise report-centric architecture, the mobile and cloud offerings. It is now a more capable product to prevent incursions in the customer base from competitors' products, and will help position MicroStrategy as a more friendly BI platform for users and developers. Going forward, it may become the standard interface for information analysis and report design.
  • There are two other forward-looking focus areas for the company: Hadoop integration — for semistructured and unstructured data analysis, and for social data leveraging — through a connector that delivers Facebook profile data to a MicroStrategy analytic application. However, they don't have as much impact in the current installed base.
  • While the MicroStrategy development environment is robust and flexible, there is a steep learning curve, even for seasoned report developers building any level of analytic complexity into parameterized reports that simulate ad hoc analysis and interactive dashboards for business users. Even though usability enhancements were delivered with MicroStrategy 9.x (such as more one-click user actions, reusable dashboards and dashboard design wizards), its customers continue to rate the platform below average for ease of use for development and ease of use for end users. Mobile BI and Visual Insight adoption should contribute to resolve the issue and change this assessment, but their relevance is still low in the overall user base. MicroStrategy needs to continue working to improve overall usability because it may be a strong contributor to the survey's low score in the achievement of business benefits — a burden common to other large vendors, which is in stark contrast to the higher scores of small vendors with simpler BI tools.
  • Although MicroStrategy has comparatively moderate administration costs per user compared with its competitors, its customers report above-average license and implementation costs per user. Moreover, "cost of software" is cited by its customers as the No. 1 product limitation to broader deployment — more frequently than for all other vendors in this year's Magic Quadrant survey (except Alteryx). Adopting MicroStrategy's Cloud Platform offering may be a way to address the issue and grow users at a lower overall cost. By bundling the different BI platform components — MicroStrategy's BI tools, partners' ETL and database software tools, and hardware and management services — customers will gain bargaining power to demand savings, but they will need to avoid vendor lock-in situations that may impact them in the future.
  • MicroStrategy's high-end halo can be a liability in an unstable economy, with companies less keen for enterprisewide initiatives and searching for more cost-efficient solutions — often business-driven departmental deployments. Visual Insight and MicroStrategy Mobile are a good fit for this purpose, but the need to also deploy core BI platform components, with their associated price tags and complexities, will reduce MicroStrategy Mobile's appeal. As a result, MicroStrategy — when acting as an all-or-nothing option — will struggle to find a position as a complementary tool in companies with competitors' platforms; in turn, it will see smaller vendors — namely from the data discovery space — do the same to its own customer base. MicroStrategy Express is a clear answer to both of these problems, but it remains to be seen whether MicroStrategy and its IT and corporate-focused sales force will be able to succeed in a business-managed, departmental BI market.
  • Conversely, the company continues to sell predominantly to IT, which has a stack-centric buying tendency. Megavendors offering end-to-end BI, CPM, packaged analytic applications and integration middleware optimized for their specific enterprise applications and technology stacks are at an advantage over MicroStrategy when stack optimization is an important purchasing criterion. MicroStrategy's focus on BI platforms excludes it from consideration, particularly in enterprise BI standardization projects wherein buyers are looking for single-stack optimizations with the existing information and application infrastructure.
  • This year's Magic Quadrant has a reinforced focus on analytic capabilities beyond descriptive and diagnostic analytics, which hurts MicroStrategy's position in Completeness of Vision and Ability to Execute. The lack of a noticeable focus on predictive and prescriptive analytics narrows MicroStrategy's breadth of use (which is already below average) to mostly reporting and dashboarding, lowers its complexity of use cases and will ultimately reduce its relevance for organizations. Although the company offers native data mining capabilities free of charge, and has delivered R language integration since January 2012, these features continue to be ignored by customers. MicroStrategy has the lowest usage of predictive analytics of all vendors in the Magic Quadrant. A reason for this behavior might be the user interface that is overfocused on report design conventions and lacks proper data mining workbench capabilities, such as analysis flow design, thus failing to appeal to power users. To address this matter, MicroStrategy should deliver a new high-end user interface for advanced users, or consumerize the analytic capabilities for mainstream usage by embedding them in Visual Insight.
  • After several quarters of good financial results, MicroStrategy had a sharp decline in sales execution in 3Q12. Changes in the sales management might be the issue that affected the company's performance, because it is difficult to establish a correlation with any other relevant fact that may be hurting MicroStrategy's position in the market. If the assumption is correct, then we should see a rebound in results in 2013, and MicroStrategy's Ability to Execute in the Magic Quadrant will also recover.


  • Oracle Business Intelligence Foundation Suite, with its principal component Oracle Business Intelligence Enterprise Edition (OBIEE), is an IT-driven, unified metadata-centric BI and analytics platform that's best suited for building large, IT-managed and centrally governed global deployments in which a broad range of BI, advanced analytics and CPM functionality from a single platform and optimization with the Oracle stack are top requirements. OBIEE customers report among the largest average deployment sizes in terms of users, data and company size, with an above-average number of respondents viewing OBIEE as their enterprise BI standard.
  • Customers choose Oracle because of its integration and optimizations with the broader Oracle stack, which are key differentiators that underpin Oracle's BI and analytics value proposition, particularly within the Oracle installed base. Specifically, Oracle BI offers more than 80 prebuilt analytic applications for Oracle E-Business Suite (EBS), PeopleSoft, JD Edwards, Siebel, Fusion (on-premises and in the cloud) and other enterprise applications, including a range of domain and industry-specific packaged analytic applications. These analytic applications include prebuilt ETL, data warehouse models, KPIs, reports and dashboards. OBIEE's analytics optimizations with Oracle Essbase and the Hyperion Enterprise Performance Management System enable customers to implement an end-to-end analytic process for the financial budgeting, planning, consolidation and close processes. OBIEE analytics optimizations with Oracle middleware and Oracle SOA Suite components, Oracle BPM for BPEL, provide integration with action links and workflow within Oracle EBS to support closed-loop insight to action analytics processes. Moreover, Oracle has planned integration between OBIEE, Oracle Complex Event Processing and Oracle Real-Time Decisions to support real-time event detection and analysis. As evidence of Oracle's strong stack value proposition, OBIEE customers in the Magic Quadrant survey choose Oracle more often than most other vendors in the survey because of its integration with enterprise applications and with the information management infrastructure (database and middleware). Furthermore, 54% of OBIEE customers have Oracle EBS as their primary ERP system (almost 3.5 times the survey average), while 80% report using the Oracle Database as their primary data warehouse (more than 2.8 times the survey average).
  • In addition to Oracle software stack optimizations, Oracle's newest engineered system, Exalytics In-Memory Machine, provides an optimized hardware and software configuration that includes OBIEE, Oracle Essbase, Oracle Endeca Information Discovery, and in-memory software (based on Oracle's acquisition of TimesTen) designed for large and complex analytics workloads, including dynamic planning and what-if and scenario analysis.
  • Oracle has long been a leader in information management and analytics for structured, mostly enterprise transaction data, but Oracle's 2011 acquisition of Endeca — now called Oracle Endeca Information Discovery — demonstrated product vision and commitment to the growing importance and potential value to Oracle customers of incorporating, relating and analyzing unstructured data for new insights. While Oracle Endeca Information Discovery platform immediately filled a gap for Oracle in business-user-oriented search-based data discovery, the more strategic road map for Oracle is to integrate Endeca assets for analyzing diverse data into Oracle's core information management, middleware and enterprise applications stack, which was recently done with EBS Extensions for Oracle Endeca. Moreover, Oracle introduced the Oracle Big Data Appliance for NoSQL and Hadoop support. OBIEE customers appear to buy into this vision, with more than 22% of them — among the highest in the survey — reporting plans to deploy content analytics in the next 12 months.
  • While Oracle offers business user search-based data discovery with the Endeca Information Discovery platform, it has been slower than its megavendor competitors to deliver business user data mashup and interactive visualization capabilities within OBIEE. Even though some additional interactive capabilities are enabled by the combined in-memory and enhanced Essbase features in Exalytics, Oracle customers rate its interactive visualization functionality in OBIEE near the bottom of the survey. Because of this limitation, as well as longer than average report development times, Oracle continues to score near the bottom of the survey for ease of use for end users and ease of use for developers. These survey results do not appear to reflect the enhancements Oracle has made to its interactive visualization capabilities in its latest releases of OBIEE and in Exalytics, since more than half of Oracle's survey respondents are not upgraded to the latest releases. Users may find improved ease of use when they upgrade.
  • Oracle has been slower than most of its competitors to deliver mobile analytics with broad device support. Mobile capabilities are currently limited to iOS devices, although Android and Windows support is on the road map. This delay appears to have caused latent demand in the OBIEE installed base, as Oracle has the highest percentage of any vendor with customers that plan to adopt mobile in the next year. Since no additional development is necessary for deploying Oracle Business Intelligence Mobile, this will facilitate adoption.
  • Oracle's customer experience ratings, which include support and product quality, as well as sales experience and performance scores, continue to be a chronic weakness. They have been consistently low for the third year in a row — and the same has been true for most of the other megavendors — with scores near the bottom of the survey. While Oracle and the other megavendors tend to have the largest and most complex global deployments, which can contribute to the relatively harsh customer assessments, other vendors with similarly large and complex deployments (like Information Builders and MicroStrategy) tend to consistently, year after year, fare much better.
  • Oracle offers a broad suite of relatively integrated, functional capabilities, placing it in the top quartile of 38 organizations surveyed for this Magic Quadrant research — when assessing the number of individual features and functions delivered by Oracle. However, an assessment of the extent to which these features meet requirements shows that customers give Oracle an aggregate product rating of below average, with a rank of 34 out of 38 vendors, with all 14 capabilities receiving a below-average functional rating score. Dashboard capabilities were the highest rated out of the 14 functional areas assessed by Gartner, with more than 65% of OBIEE customers using it extensively.
  • OBIEE is primarily used for systems of record, static and parameterized reporting, as well as dashboards centrally developed by IT and delivered to report consumers, leading to a below-average complexity of user analysis ratings. OBIEE customers report that, on average, 70% of OBIEE users are consumers or casual business users, with 86% of users viewing static or parameterized reports. While Oracle offers data scientist and developer-oriented predictive and prescriptive analytics capabilities that are similar to deployment patterns in the broader market, they are not widely adopted. Making more complex types of analysis and advanced analytics more broadly accessible to business users is a major driver of growth in the BI market — a trend that Oracle has been slower to fully address than other stack vendors.

Panorama Software

  • Panorama is considered the standard BI platform for 84% of references — the top score in the survey and a significant result for the company. Panorama Necto, introduced in 2011, replaced the NovaView platform and is built around a framework of social BI — with collaborative decision capabilities and contextual discovery — automatic push of relevant insights according to users' preferences and past behavior, and consumerized analytics — allowing users to look for cause-and-effect correlations in business metrics. The migration to Necto is reported as straightforward, and this year's Magic Quadrant survey has 76% of Panorama's references already using it, which drives the assessment results.
  • Panorama received top scores in a significant number of areas, such as integration, including consistent interfaces and a unified semantic layer leveraged across the platform tools, good integration with complementary BI capabilities, search, content management, common security and a single administration application across components. Ease of use for end users is in the top quartile and ease of development is No. 2 — only surpassed by Tableau Software in this Magic Quadrant. The survey results for functionality are also very positive, with Panorama achieving the second best overall results, only behind Birst. As a consequence, the company's Completeness of Vision has improved significantly, moving Panorama closer to the Visionaries quadrant.
  • With regard to how customers apply the product, it continues to be used primarily as a front end for OLAP databases — chiefly Microsoft SQL Server Analysis Services — via MDX. However, users' activity goes well-beyond this and shows a more forward-looking profile than what we observe with most other vendors. There is relevant adoption of personalized dashboards, in-memory interactive exploration and analysis of data, predictive analytics and/or data mining, content analytics, access and analysis of unstructured external data (for example, social network data) — the highest in the survey — and collaborative decision making. Moreover, 21% of respondents also reported they were actively using mobile BI, and 26% had plans to deploy a public, private or hybrid cloud solution in the next 12 months — Panorama provides a cloud solution supported by Microsoft's Azure. Such a usage landscape clearly goes beyond traditional BI into areas of increased potential differentiation and innovation for its customers.
  • This year, the top reasons why customers choose the software are ease of use for end users and developers, performance and collaboration — Panorama has the widest use of collaboration capabilities in the Magic Quadrant, which confirms it as a sales driver capability. In this area, Necto introduced a number of social network features, such as the ability to "follow" another user and be informed of his or her information sharing activity, to "post" new analysis that others can see and respond to, to write "comments" on other people's analysis, to "like" a co-worker's dashboard or to create a "hangout" with a team to discuss a specific insight — all of which observer a proper security model. This works as a clear differentiator for Panorama and, in customers where it receives adoption and creates the effect of a BI-focused social network, it's less likely that users will want to discontinue the product.
  • Geographical presence is still a major issue for Panorama and affects its Ability to Execute in the Magic Quadrant. Fifty-three percent of customers are located in the Middle East, 16% in Europe and 13% in North America. This represents the legacy of its original home market, but also shows that the company is not growing fast enough elsewhere. A small team of dedicated sales representatives may need to be expanded to leverage the product that the company has developed. The partner network should also be re-examined to ensure more solid growth in the U.S. and Europe.
  • A historic value of 86% product renewal rate is below the market benchmark and should be a concern for the company. In this year's survey, the company has 5% of customers planning to discontinue the product within the next three years — although this is better than the past, it still needs to improve. Panorama Necto may recover this key metric, which was a sign of low satisfaction with the former platform, NovaView.
  • Reference customers continue to flag some concern over the suite's reliability and/or stability. The feedback has improved, though, with the product quality score no longer a major barrier preventing further deployment. The product support has also recovered and is aligned with the market in this survey, after action was taken by Panorama in the past two years.
  • A strong reliance on Microsoft, with Panorama products targeted at SQL Server, SharePoint, PowerPivot and Azure, is an opportunity for sales due to the large installed base of customers — but it's also a risk. Microsoft is showing a strong Ability to Execute and has an ambitious road map for the future. We may see more Microsoft customers getting to a point where they don't feel the need for BI companion solutions, because the capabilities available are good enough to fulfill their companies' needs. Panorama needs to ensure that it can thrive in direct competition with its master partner.


  • This is Pentaho's second year in the Magic Quadrant. It provides a comprehensive, end-to-end open-source BI solution. Pentaho Business Analytics is a data integration and BI and analytics platform composed of ETL, OLAP, reporting, interactive dashboards, ad hoc analysis, data mining and predictive analytics, all of which are managed from a central BI server deployed on-premises or in the cloud, with end-user access available via the Web or mobile devices — including the iPad with content authoring enabled.
  • Customers choose Pentaho for its data access and integration, where it ranked second highest on the reference survey for customers citing this attribute as a reason for vendor selection. This makes sense, given Pentaho's broad connectivity to a diverse set of structured and unstructured data sources, including a standard database management system like Oracle, DB2, SQL Server or MySQL; and native connectivity to Hadoop-based systems such as Apache Cloudera, Hortonworks and MapR; NoSQL databases like Cassandra, HBase and MongoDB; and analytic databases like Vertica, Greenplum and Teradata; as well as cloud applications, such as and Amazon Web Services.
  • Customers also choose Pentaho for its overall TCO, where it ranked third highest on the reference survey for customers citing this attribute as a reason for vendor selection. Low license cost is central to Pentaho's value proposition.
  • Pentaho is gaining traction in big data deployments. Pentaho added native integration with major big data sources — such as 10gen MongoDB, Cloudera and DataStax — and improved runtime performance for Hadoop from its unique data integration engine, which can be deployed to individual nodes in a Hadoop cluster. Big data deployments tend to be only in the high end of the market, but there have been some customer success stories. Examples include e-commerce companies with personalized promotions and cross-sell use cases derived from large volumes of clickstream data from e-commerce companies' Web properties, emails and social sites.
  • Other major improvements in 2012 included building a visual design environment to increase developer productivity. For data analysts and scientists, Pentaho introduced Instaview, an interactive data discovery and exploration application, to analyze large volumes of complex and diverse data, and to continue its investment in predictive analytics. Pentaho also delivered an optimized mobile experience with native gestures and touch-enabled drag and drop.
  • Pentaho's lightweight footprint, in which the complete platform can be deployed in a small environment on a laptop, or can be integrated into an existing scalable architecture (such as a grid for much larger deployments), makes it very flexible in meeting a broad range of deployment requirements. Moreover, Pentaho is an embeddable platform, making it very attractive to ISVs and internal IT shops for embedded use cases, which continue to compose a significant portion of its business to deploy on-premises and in the cloud. Its cloud initiative is showing momentum. Twenty percent of customer references indicated using Pentaho through a private cloud, and 11% planned to deploy it through a private cloud in the next 12 months.
  • When asked about problems with the software, Pentaho had the highest percentage of references citing absent or weak functionality, and a reasonably high percentage indicated that it was difficult to implement, unable to handle the required data volumes and unable to support large numbers of users. When asked about product-specific limitations to wider deployment, Pentaho ranked third highest among vendors whose references cited ease of use for business users, and second highest among vendors whose references cited ease of use for developers.
  • Pentaho is also below average on 10 of the 15 capabilities reviewed in this survey: reporting, ad hoc query, dashboards, interactive visualization, Microsoft Office integration, metadata management, collaboration, search-based data discovery, predictive modeling and data mining. However, this is an improvement over last year's survey, in which Pentaho was below average across all capabilities except predictive modeling. In particular, Pentaho's customers are less likely to be using mobility actively. However, they are more likely to deploy it in the next 12 months, compared with the market average.
  • The open-source community gives Pentaho access to resources beyond what might be expected for a company of its size. However, even with its extended resources, Pentaho is small relative to the leaders in this space, with fewer resources to both enhance its core BI platform so that it is on par with commercial equivalents, and to differentiate itself through innovation. Moreover, its vertical strategy and global reach for its commercial product are more limited than most of its larger commercial competitors. However, last year, Pentaho received a $23 million infusion of venture funding. With additional funding, Pentaho is expanding its sales force and investing in engineering to continue to innovate in big data, cloud and embedded analytics.


  • Founded in Perm, Russia, in 1991, Prognoz now has regional operations in Africa, Europe, Asia and North America. Its product, the Prognoz 7 Platform, is a unified platform with analysis, reporting, OLAP, dashboarding, modeling and predictive analytic capabilities. The company largely develops specific analytic applications on a consulting basis with its clients. Eventually, those applications are extended and new applications are built by client organizations. Prognoz has very large deployments. In the survey, Prognoz references averaged 2,311 users, which is significantly higher than the average of 1,249 users across the industry.
  • In its second year of evaluation in this Magic Quadrant, customers scored Prognoz particularly well on the reference survey. This, coupled with some major investments Prognoz made in 2012 to expand geographically, caused it to move significantly toward the high end of the Niche Players quadrant. While Prognoz has more than 100 international clients, it isn't well-known as a BI and analytics platforms vendor outside Russia, where it maintains a dominant market share. Prognoz is making investments globally, and in 2012, a primary success was establishing a development and sales office in Zambia, which led to the vendor closing a significant number of deals with the federal governments in several African nations.
  • Customers choose Prognoz most often for its functionally, skills availability (company consultants), ease of use and strong support. Prognoz ranked in the top quartile among vendors whose references indicated functionality as the primary reason for vendor selection. Its statistical capabilities were bolstered this year with a more sophisticated predictive analytics engine focused on econometric and time series modeling. Beyond product functionality, a significant number of Prognoz customers cited availability of skills and overall vendor support capabilities as primary reasons for vendor selection.
  • The company's consultative approach is obviously well-received. With hundreds of development resources available in Russia, the company is exceptionally responsive to customer requirements. Prognoz's ability to build specific analytic applications for its customers, using its software platform and leveraging numerous internal consultants available around the globe, has created a unique go-to-market strategy and enabled it to win deals in significant customers' sites, such as the International Monetary Fund and the World Bank. These targeted analytic applications have become widely deployed. Prognoz averaged almost double the market average number of BI and analytic uses, compared with other vendors in the market. This is a significant improvement over last year's customer reference survey. Moreover, many of these applications built by Prognoz consultants are customer-facing, and are enriched with data from external sources. Prognoz ranks No. 1 across all other vendors on these criteria.
  • Only 20% of customer references considered Prognoz to be their BI standard, which ranked the company in the lowest quartile for this question. References reported that expansion is often blocked when there is limited buy-in to an enterprise approach to business analytics. Conversations with references indicated that the product may be purchased and deployed for a specific use case — for example, econometric analysis — but not for general business use. Twenty-six percent of its customers said the inability to gain user buy-in to an enterprise approach was a limitation to broader adoption.
  • Prognoz's consulting-led approach, while a benefit to some, significantly limits it as a free-standing, customer-implemented BI platform. The company has made strides recently in building out functionality to make the tool more approachable to client BI developers, but existing customers consistently report that ease of use for developers is a concern. In Gartner's opinion, this is the company's main challenge to competing in the BI and analytics platforms market.
  • Prognoz has established a strong presence in Russia, other parts of Asia and now Africa, but it has a very small presence in Western economies. Despite its relatively high revenue base and growth, Prognoz is still in the very early stages of building out its presence in the U.S. and in Western Europe. Local capability is expanding as opportunities are closed, but there remains a high dependence on resources from headquarters to support local projects. It will take time for the company to replicate its home market success in other geographies.


  • QlikView, QlikTech's product, is a market leader in data discovery, a segment of the BI market it pioneered. QlikView is a self-contained BI platform, based on an in-memory data store and newly added direct query access (currently to Teradata, Google BigQuery and Cloudera, with more sources to come in the near future), with a set of well-integrated BI tools. Customers choose QlikView because of its intuitive interactive experience — most often deployed in dashboards — that enables business users to freely explore and find connections, patterns and outliers in data without having to model those relationships in advance. QlikTech earned top rankings for the percentage of customers that choose the platform for ease of use for end users, with an above-average percentage selecting QlikView for ease of use for development, and the highest percentage of customers of any vendor choosing QlikView because of implementation cost and effort.
  • QlikView's ease of use is coupled with above-average complexity of the types of analysis users can conduct with the platform, and an above-average breadth of functionality used. QlikTech's customers also report achieving above-average business benefits, particularly in making better information available to more users and in expanding the type of analysis undertaken. This powerful combination of advantages has been a key driver of data discovery vendor success in general, and of QlikView in particular.
  • QlikView's interactive experience is enhanced by its in-memory computing model. QlikView customers report near the top of the survey's performance scores (albeit on smaller-than-average data sizes), although this differentiator is narrowing since most of the BI vendors now deliver in-memory capabilities.
  • QlikView customers have a positive view of seven out of 14 functional capabilities rated in the Magic Quadrant survey, including reporting, ad hoc analysis, dashboards, interactive visualization, scorecards, search-based data discovery and mobile BI. The top reasons for choosing QlikView are: (1) functionality; (2) ease of use for end users; and (3) performance. A positive product experience has contributed to QlikView customers having a positive view of its future. QlikView has among the smallest percentage of customers that plan to discontinue using the product in the future, and report among the top success scores — which are defined as expanded user deployments — of any vendor in the survey.
  • QlikTech's acquisition of Expressor and the subsequent release of QlikView's Governance Dashboard give QlikView customers a way to identify and resolve the use of multiple definitions deployed across existing QlikView applications, and to create reusable metadata components for new development. The lack of these capabilities had often prevented it from being considered as an enterprise standard, and from winning large enterprise deals. Now, QlikView has a compelling approach to govern data definitions without sacrificing business user development flexibility to build applications, and without having to wait for centralized IT to first build a semantic model. This was also a necessary addition to QlikView's portfolio to compete against the enterprise IT-centric BI vendors, which have added data discovery features to their platforms.
  • QlikTech, which was founded in Sweden, has been successful at globally expanding its market reach and awareness beyond its traditional stronghold in Europe to North America. It has also been successful at growing regions in Asia/Pacific and Latin America. QlikTech has a large and global partner ecosystem, particularly when compared with its stand-alone data discovery vendor peers.
  • Customers most often select QlikView for ease of use for end users, particularly for interactive dashboards; however, the visual-based interactive exploration and analysis capabilities, experience, and time to business user authoring proficiency are generally viewed as inferior to those of its stand-alone data discovery competitors, Tableau and Tibco Spotfire. The next major release of QlikView, which is due for launch in 2013, places major emphasis on addressing this competitive limitation with a major design theme focused on delivering a "gorgeous and genius" experience. While a major update to the platform will help QlikTech better compete against the stand-alone data discovery vendors, as well as against the enterprise features of the traditional BI players (for example, Microsoft, SAP, IBM, Oracle, Information Builders and MicroStrategy), it is not without the risk of disruption for customers at a time when QlikTech is also facing a more intense competitive landscape from these same vendors.
  • While Gartner estimates that the data discovery segment grew at three times the rate of the overall BI market in 2011, and QlikView was the leader in this segment, data discovery capabilities are now becoming mainstream. The market is more crowded with existing, stand-alone vendors becoming more competitive, new vendors emerging, and all leading BI vendors having added data discovery capabilities to their IT-centric platforms in 2012 as an integrated, and often bundled, license-cost-free feature, with the intent of narrowing QlikView's (and the other stand-alone data discovery vendors') opportunities for expansion.
  • Enterprise readiness and user scalability are ongoing concerns. QlikView earned below-average customer survey scores on enterprise features, such as metadata management (we expect this assessment to improve as adoption of Expressor spreads among QlikView customers), BI infrastructure and BI development tools. Additionally, customers and implementers continue to express concerns over QlikView facilities for managing security and administering to large numbers of users. Scaling QlikView to more users, larger data sizes and more complex dashboards is directly correlated with hardware resources, such as RAM and processing power. While QlikView user deployment sizes and average data sizes continue to increase, they are still below the survey average and below its data discovery competitors. QlikView data sizes, although slightly up from last year, may have been limited by QlikView's in-memory-only approach versus competitors that could directly query and bring in data from warehouses well before QlikView's recent Direct Discovery capability was available. With QlikView's newly added capabilities, data scalability should increase, while QlikTech's acquisition of Expressor should address metadata concerns. Moreover, the rearchitected version of QlikView that's planned for 2013 is intended to significantly enhance a range of enterprise development and scalability features.
  • Customer experience results, while improved from last year, are a mixed bag. QlikView earned positive product quality scores, and a smaller percentage of customers reported problems with the software, which resulted in an overall above-average customer experience score. However, QlikView continued to suffer from just below the survey average (third quartile) support scores. Similarly, sales experience continues to be below the survey average. Gartner inquiries suggest that the direct sales team is often perceived as inflexible and unresponsive. We continue to believe that these results can partly be affected by QlikView's rapid growth, since support and sales proficiency are highly correlated with length of tenure. High growth means a larger percentage of relatively new sales and support people. However, we expect to see continued improvement next year (as we did this year) as QlikTech scales its processes to support growth, a broader partner channel and expansion into larger enterprise deployments.
  • QlikView customers often express concerns over the scalability of its predominantly named user pricing model. Cost of software is reported as the largest barrier to broader deployment by companies that have implemented QlikView. While named user pricing has the advantage of giving every QlikView user access to full authoring capability, it is relatively costly on a per-user basis for a very large number of users when compared with many competing alternatives. This pricing model well-supported QlikTech's departmental "land and expand" sales approach, which allowed the company to add 100 seats at a time, department by department, with minimal discounting. However, as QlikTech seeks more enterprise deals, and as procurement departments begin to manage QlikView purchases across departments, the pressure to discount has increased. Despite its strong market position and compelling value proposition, it is likely to be increasingly difficult for QlikTech to defend its premium price position as it competes for larger deals, and as competition from bundled enterprise alternatives intensifies.
  • QlikView users reported among the longest report development turnaround times — particularly for building large, complex reports from various data sources, involving detailed logic and calculations — of any vendor in the Magic Quadrant. We expect this to improve as the next version of QlikView rolls out more enterprise features targeted at developer efficiencies, and as more of its customers adopt Expressor and take advantage of reusable metadata components, rather than having to script the data integration for each QlikView application.
  • A below-average percentage of users claim they are using QlikView for static reporting, indicating that this falls outside of QlikView's sweet spot. Customers that need a range of systems of record reporting and interactive dashboards and visualization from a single tool are less likely to choose QlikView.

Salient Management Company

  • Salient bolsters its general-purpose data discovery architecture with vertically specific solutions. With its in-memory model and visual data mining, Salient offers an unfettered drilling experience, giving users control of all relevant data and making it a compelling option simply for its horizontal data discovery architecture. However, the reality is that more than three-quarters of Salient's customers use it as part of a packaged vertical application. Salient is one of the few organizations in the BI and analytics platforms space that has equal depth in the software technology and the business acumen required to integrate this technology into the mainstream business decision-making process of organizations. In particular, Salient is strong in the beverage and consumer goods industry, especially for revenue management applications, such as sales forecasting and margin analysis. Recently, though, it has been making strides in the state government and healthcare spaces, delivering analytical solutions to identify potential instances of waste, fraud and abuse, particularly in the combination of clinical, financial and insurance claims data.
  • According to the reference survey, customers choose Salient for its ease of use (report development time is significantly better than average), data access and integration (above-average percent of data integrated from external sources), query performance (leveraging its UXT in-memory technology) and overall product quality (bug-free code). Salient's customers ranked it above average for 11 of the 15 capabilities evaluated in the survey.
  • Beyond product features and functionality, customers also value the close relationship Salient establishes with its customers — this is reflected in Gartner's customer reference survey, where Salient ranked second highest for overall sales experience and above average in every other customer-support-related area, including overall customer support, level of expertise, response time and resolution time.
  • Most Salient end users are power users doing moderately complex to complex analysis. Salient's customers cite write-back and constraint-based modeling functionality as one of Salient's key strengths. The ability to perform scenario modeling and support-planning-type use cases is rare in in-memory BI products, which tend to focus on ad hoc "slice and dice"-type interactions. In addition to handling complex calculations (for example, key performance metrics, productivity metrics, price elasticity and allocations), Salient users are typically integrating multiple sources of data. According to the survey, Salient customers were more likely to perform ad hoc analysis and moderately complex analysis on data that has been joined from multiple data sources.
  • As mentioned above, Salient is a data discovery architecture primarily for power users, not information consumers. Based on our customer reference survey, Salient customers have significantly fewer overall users, compared with other vendors' customers. In addition, Salient customers have fewer external users, and users as a percentage of employees. Last year, Salient made investments to overcome this concern by releasing its Collaborative Intelligence Suite v.5, which represents a major shift in emphasis from Salient's typical focus on individual analysis to a more collaborative environment in which each member of the enterprise, from senior executives to any knowledge worker, has access to information. These efforts are needed to help Salient be viewed as a more comprehensive BI and analytics platform. Currently, Salient is (slightly) below average among customer references ranking Salient as their enterprise standard BI and analytics platform.
  • While Salient customers generally scored the technology and the platform positively, there were a few capabilities that Salient customers rated as below average, including dashboards, BI infrastructure, Microsoft Office integration and mobile BI. The survey also showed that fewer Salient customers used the dashboard and mobile BI capabilities, compared with other vendors' customers. Salient has addressed these technical concerns with its new release by adding: (1) new drillable dashboards that are fully integrated into its in-memory database; (2) the ability to integrate using proprietary or standard ETL technologies; (3) new reporting features; and (4) a new concept called "storyboards," which allows information consumers to perform complex analysis along predefined paths, without the training necessary to become power users. Beyond these individual feature concerns, Salient's proprietary data discovery architecture is the reason behind its strong reputation for ease of use.
  • Despite increased marketing investments in 2012, Salient is not very well-known in the market. Salient is primarily a North American vendor with a limited sales presence, a small partner ecosystem and few global resources. In 2012, Salient began building out a partnership network to drive growth; now, it has partners in the Middle East, Asia, Latin America, Africa and Australia, and these efforts are gaining momentum.
  • To date, Salient's strategy has never been about rapid growth and expansion, because that would jeopardize its reputation for tight customer relationships. However, given the emphasis on the data discovery architecture, Salient has a valuable offering — heavily sought after by numerous potential channel partners — that could jump-start growth considerably. In particular, Salient should take advantage of the emerging data-as-a-service trend and find partners that are delivering industry-specific data services that could leverage Salient's platform and vertical domain expertise.


  • SAP is the global market share leader of the BI and analytics platforms market. Its large customer base is indicative of future maintenance revenue, which can be allocated to R&D and merger-and-acquisition initiatives to drive products forward. SAP's market share dominance shows in its high proportion of large enterprise deployments. SAP customers average twice as many users as the market average across all vendors. SAP is frequently cited by customers as the enterprise standard BI and analytics platform. SAP's propensity to be the enterprise standard extends to the breadth of deployment. When asked how extensively this BI vendor is deployed — from departmentally to globally deployed — SAP ranked No. 1 across all 38 vendors surveyed in Gartner's most recent customer survey.
  • Based on evidence from Gartner inquiries, SAP closed a significant number of multimillion dollar deals in 2012. Its substantial commercial success is largely due to its product marketing efforts targeting the SAP enterprise application base, as well as its capabilities for large enterprise deployments, as indicated in the survey. The aggressive bundling and stack-centric messaging has resulted in strong product sales. Compared with the average across all vendors, three times the percentage of SAP customers cited "integrates with enterprise applications" as one of the top reasons for choosing the vendor.
  • SAP has one of the largest global direct sales, support, channel and service ecosystems. The major system integrators all have large SAP and BusinessObjects practices. This strength will be particularly helpful as SAP applies its BI solutions to specific industry business processes and domain-specific analytic applications. It also provides access to skills on a global basis for different industries and companies of different sizes. Access to people (internal or external) who know SAP BW or BusinessObjects is rarely difficult. SAP scored well-above average, compared with other vendors, when customers were asked if access to skills was one of the most important reasons for choosing the vendor.
  • SAP responded to the market's changing dynamics by investing in a nascent data discovery offering, SAP Visual Intelligence. This was initially limited to just Hana as a data source, but is now able to access a variety of data sources, and to take advantage of SAP's data acquisition, enrichment, and transformation capabilities, which were designed for ease of use by mainstream business users.
  • While it has been in the mobile BI space for more than 10 years, in 2012, SAP enhanced its mobile experience with geospatial and camera capabilities, enabling users to view information in camera view over the visual representation. SAP offers an integrated mobile BI toolkit so that developers can leverage the SAP Mobile Platform, (formerly known as Sybase Unwired Platform), thereby offering customer mobile analytics app design, device management and device security. Also, with the latest release of SAP BusinessObjects BI 4.0 Feature Pack 3 (FP3), SAP offers full 2-way integration of SAP StreamWork into the BI platform, allowing users to see decisions in which BI content is being leveraged and request participation, or to follow the progress if they are already included.
  • SAP Predictive Analysis, introduced in 2012, bolstered its predictive analytics offering by integrating analytical capabilities already built in R with the real-time and in-memory capabilities of Hana to create some new, advanced analytic use cases. By leveraging its Data Services integration with Hadoop, Hive and other big data processing and map-reduce technologies, SAP is able to store this information inside SAP Hana and provide analytic applications on top, including CO-PA Accelerator, Customer Segmentation Accelerator, and Business Planning and Consolidation.
  • When respondents were asked which product-specific limitations were barriers to wider deployment, more SAP respondents cited software quality than for any other vendor. Of all SAP's references, 20.17% cited this limitation, compared with an average of 6.2% across all vendor references. When asked about problems with the software, a greater percentage of SAP references cited "unreliable, unstable and/or buggy" than for any other vendor in the Magic Quadrant. Much of this poor product quality can be attributed to the challenge of integrating and supporting multiple code bases, such as BW, Web Intelligence, Crystal Reports and Dashboards. However, there is significant improvement within references running later versions. For example, 29.63% of SAP BusinessObjects XI 3.1 references cited this problem, compared with just 16.67% of SAP BI 4.0 FP3 references.
  • In addition to poor product quality, customers have complained about unsatisfactory support. In our latest survey, SAP ranked last in customer experience and sales experience. Unfortunately for SAP customers, it isn't a matter of just one bad year, because SAP has consistently ranked at or near the bottom of customer support since Gartner started this series of surveys in 2008. However, there has been some improvement. SAP BusinessObjects XI 3.1 references averaged 4.32 (on a scale of 1 through 7) for its support rating, compared with an average of 5.0 among SAP BI 4.0 FP3 references. Nevertheless, both groups scored below the 5.71 average across all vendors' references. The same is true for the sales experience score. SAP BusinessObjects XI 3.1 references averaged 4.15 (on a scale of 1 through 7), compared with an average of 4.94 for SAP BI 4.0 FP3 references. While there was improvement, again, both groups are well below the 5.77 average across all vendors' references.
  • When compared with other vendors in the survey, SAP scored below average across all 15 BI platform capabilities evaluated during the Magic Quadrant research process. Of those capabilities, SAP BusinessObjects customers identified reporting and ad hoc query functionality as the platform's top strengths. SAP customer references using SAP BI 4.0 FP3 scored product functionality and overall product satisfaction much higher than SAP customers that were not running the very latest release. For example, references running 4.0 FP3 rated SAP's ad hoc query capability 8.75 on a scale of 1 through 10, compared with references running SAP BusinessObjects XI 3.1, which rated ad hoc query only 7.74 on the same scale. Microsoft Office integration was rated 8.10 across all SAP BI 4.0 FP3 references, compared with SAP BusinessObjects XI 3.1 references, which rated this capability 7.05. Comparing references across versions also saw a wide variance for the mobile BI capability. SAP BusinessObjects XI 3.1 references rated this capability 5.9, while SAP BI 4.0 FP3 references rated it 8.10.
  • This pattern of SAP's FP3 references scoring better than SAP's legacy customers (but still below the industry average) occurs in several other areas. For example, when references were asked about complexity of migration on a scale of 1 through 4 (with 4 being the most complex), SAP BusinessObjects XI 3.1 references scored 2.67, compared with SAP BI 4.0 FP3 references, which scored 2.06 (lower is better, but still below the industry average of 1.65 across all vendors' references). When asked about the average number of days to create a report, SAP BusinessObjects XI 3.1 references averaged 6.77 days, compared with 5.43 days for SAP BI 4.0 FP3 references. Keep in mind that the overall average across all vendors' references was just 3.95 days.


  • SAS's portfolio includes tools in areas such as BI, performance management, data warehousing and data quality; however, unlike most other BI platform vendors, SAS primarily focuses on advanced analytical techniques, such as data mining and predictive modeling, where references acknowledge it as a leader. SAS's clients report the use of large datasets and perform analysis with above-average complexity. They also access and interpret unstructured internal and external data more often than most vendors' clients surveyed for this Magic Quadrant. Such positioning benefits SAS in this year's Magic Quadrant, where basic BI capabilities got a lower weighting than in previous years.
  • SAS gets high marks for its global footprint and broad industry initiatives. The solution-oriented analytic application approach to the market is a differentiator, giving the company the advantage of having a wide variety of cross-functional and vertically specific analytic applications out of the box for a wide variety of industries, including financial services, life sciences, retail, communications and manufacturing. Thus, SAS's sales processes can be diverted from tool features and price comparisons to a discussion of potential business value of solutions and industry expertise. While others are also adopting this approach, SAS remains in the lead.
  • In 2012, SAS announced Visual Analytics, the new data discovery product that merges dashboard design with diagnostic analytics and the use of predictive models — a possibility not yet available in some of its competitors' tools. Visual Analytics also provides mobile BI capabilities — a gap that, until now, had been resolved through a partnership with MeLLmo Roambi. Moreover, it is the first visible result of a comprehensive initiative to standardize user interfaces and to better integrate the product portfolio — an area where SAS scores lower than most other vendors in the Magic Quadrant survey. For SAS, it's also a key instrument to reach beyond analytics experts to a more mainstream audience, thereby preventing competitors' data discovery tools from doing so on its customer base. With the aggressive pricing and strong push being made by the company on what looks a promising product, we expect to see good customer adoption in the coming months.
  • Data access and integration and the capability to support large volumes of data are the primary drivers for adoption, according to the survey. SAS's recent efforts around its High-Performance Analytics Server for in-memory, in-database and grid computing analytics will likely reinforce this trend. Availability of skills is also cited — the result of a wide and loyal user base, many of whom have built careers around these products. A broad sales and service ecosystem, coupled with above-average results on sales relationship and positive survey references for product road map and future vision, will continue propelling SAS. Reference customers confirm this by predicting a positive outlook for SAS's success within their organizations, as well as in the market as a whole.
  • References continue to report that SAS is very difficult to implement and use — it was the No. 3 vendor in both categories. Aggravating this, although it has a worldwide network of support centers and an extensive list of service partners, SAS's customer experience and product support are in the lower quartile of vendors in the Magic Quadrant. A revision of user interfaces and an enhancement of product integration is under way to help improve the customer experience, but SAS must also improve its level of service — including level of expertise, response time and time to resolution.
  • SAS's dominance in predictive analytics and statistics continues to be challenged on many fronts. IBM is still the main challenger with SPSS and other analytic assets, but wide support of open-source R by large competitors, such as Oracle, SAP and other smaller vendors, will be the most serious threat in the long term. R is challenging SAS for the title of standard coding language for analytics, and is increasingly considered a credible alternative by professionals in the market, eroding SAS's dominance in the analytics community. Other vendors, such as Kxen (not included in this Magic Quadrant), Prognoz, Alteryx or Tibco, are additional sources of competition as more customers adopt analytics. These hardened challengers may not be a severe problem for SAS, however. The growing analytics market is a "rising tide" for every participant, and SAS, being the experienced leader, will be able to capture a significant share of it.
  • Customer references report that cost is the most common factor blocking further adoption, and they cite low results in the achievement of business benefits. Moreover, they mention — three times more than the average — the inability to gain user buy-in to an enterprise approach. With more options available, these factors may lead to a growing adoption of tactical analytics solutions from smaller vendors. SAS should remain responsive to customers and prospects in these areas.
  • Despite SAS's success and awareness as a leader in the predictive analytics space, the company is still challenged to make it onto BI platform shortlist evaluations when predictive analytics is not a primary business requirement. It's significant that less than 50% of references — compared with 60% from last year — indicated that SAS was their company's BI standard. Functionality used in traditional BI areas (reporting, dashboards, OLAP and so on) was lower than for other BI leaders in this research. Like last year, ad hoc query remains the one exception, with clients aggressively using SAS BI for that component.

Tableau Software

  • Tableau has the intuitive, visual-based, interactive data exploration experience that customers love to use and competitors love to imitate. Customers continue to be exuberant with Tableau, particularly around its core differentiators — making a range of simple to complex types of analysis accessible, easy and fun for the business user. Because of its strong and sustained market understanding (as defined by meeting the overwhelming customer requirements for ease of use, breadth of use and growing deployments), its competitive differentiation and strength against installed base traditional IT-centric vendors as well as data discovery market segment competitors — which has resulted in its accelerated customer and market momentum, as well as an above-average product vision — we have moved Tableau into the Leaders quadrant for the first time this year.
  • Tableau is a self-contained BI platform that provides purpose-built, business-oriented data mashup ETL capabilities with direct data connectors that leverage Tableau's VizQL technology (drag-and-drop operations in Tableau create a query in VizQL, which interprets and packages an SQL or MDX query to the database, and then expresses the response graphically). Direct query access has been a strength of the platform since the product's inception. Tableau has a broad range of support for direct query SQL and MDX data sources, as well as a number of Hadoop distributions. Its columnar, in-memory data engine, which can be used as an alternative to or in hybrid mode with its direct query access, enables fast performance on large and multisource datasets, and on complex queries, such as very large multidimensional filters or complex co-occurrence or multipass queries. A zero programming data mashup capability, combined with an in-memory database, allows users to blend and visually analyze large amounts of diverse datasets with autodetect relationships between multiple sources (of any format). This allows users to connect to and combine any data source and produce a series of interactive dashboards. Interactive analysis can be shared with a report consumer equipped with a Web browser. In Tableau 8, a user can also build an interactive analysis from a browser, including from a mobile device. Tableau users also report among the lowest times to implement, the fastest report and dashboard development times across all levels of complexity, among the highest percentage of business user authors of all users of any vendor in the survey, and among the highest business benefits achieved. The combination of exceptional ease of use (users often describe Tableau as "fun") with the ability to conduct sophisticated analysis explains why users are particularly pleased with Tableau.
  • Tableau is one of a number of stand-alone BI vendors delivering strong, interactive visualization for analysis, dashboards, information delivery and managed analytic applications. Tableau's strong performance, even with an increasingly crowded competitive landscape, is evidence of its ability to meet the sustained and predominant market demand for easy-to-use and intuitive interactive BI tools that are easy to deploy without IT assistance. While Tableau initially received collateral benefit from QlikTech's successful market awareness activities, it is now driving its own awareness, resulting in strong market momentum. Survey customers cite ease of use for end users and developers, as well as functionality, as the key reasons for choosing Tableau. In fact, customers rate Tableau as No. 1 of all vendors surveyed for being selected for ease of use for developers and end users. From a functional perspective, Tableau continues to garner above-average ratings in reporting, ad hoc query, dashboards, scorecards, and mobile with interactive visualization ratings. Tableau's sweet spot is second only to Birst in this year's survey. Customers continue to have an overall positive customer experience, rating Tableau above average for support, sales experience and performance. Although these scores are lower than the past two years, Tableau's product quality ratings continue to be at the top of the survey, with an above-average percentage of Tableau's customers reporting that there are "no product issues to broader deployment," which is a key measure of satisfaction with customer experience. Moreover, despite frequent new product releases requiring customers to upgrade, Tableau's customers report among the lowest scores for migration complexity, with more than 80% rating the product extremely straightforward or straightforward to migrate, and among the highest percentage of customers (more than 90%) have already migrated to the latest release of the software. The combination of these results explains Tableau's strong Ability to Execute position, despite its relatively small size when compared with other Leaders.
  • Tableau's implementations continue to feature larger data sizes, including unstructured data from a range of Hadoop distributions and search-based index vendors, such as Attivio. This year, Tableau references were among the highest in the size of data they analyze, with among the highest percentage of customers in the Magic Quadrant survey reporting that they use Tableau to analyze unstructured data, and among the highest percentage of users reporting that they plan to do so in the next 12 months. Moreover, Tableau has an above-average percentage of external users accessing externally facing Tableau applications. This is largely due to Tableau's SaaS offerings, Tableau Public and Tableau Digital, which have enabled websites (such as CBS Sports' Fantasy Football and Baseball, Microsoft's Windows Azure Marketplace DataMarket and other news, media, entertainment and government websites that embed Tableau Public visualizations) to share data in engaging ways with their audiences. While overall intentions to adopt BI in the cloud are around 30% of survey respondents, Tableau customers have above-average intentions to use Tableau in the cloud in the next 12 months. This high-leverage, go-to market approach also contributes to Tableau's strong market awareness, and has the potential to expose substantially more users to Tableau products (to further drive Tableau's momentum) than its traditional direct channels would.
  • Direct query access optimized for many diverse data sources has been a strong feature of the platform since its beginnings, contributing to the platform's ability to analyze large datasets. This has been a differentiator for Tableau, particularly against the stand-alone data discovery vendors, QlikTech and Tibco Spotfire, which only recently added direct query access. As evidence of Tableau's direct query adoption, its customers use it to analyze data in a broad range of vendors' EDWs (Oracle, Microsoft SQL Server, IBM DB2 and Netezza, and so on). For example, 13% of Tableau customers use Teradata as their primary EDW, which is approximately 2.5 times the survey average, higher than any other vendor in the survey (except for MicroStrategy). As Tibco Spotfire and QlikTech direct query support matures, we expect this differentiation for Tableau to decrease.
  • Tableau's user counts grew by 75% from last year, but the platform is still largely departmentally deployed, albeit across multiple departments, with just below the survey average for user deployment size. Tableau's products often fill an unmet need in large organizations that already have a BI standard, which makes them frequently deployed as a complementary capability to an existing BI platform. As a result, Tableau is still less likely to be considered an enterprise BI standard than the products of most other vendors. Given the success of Tableau and other interactive visualization vendors, leading traditional BI platform vendors — including Microsoft, MicroStrategy, IBM and SAP — delivered their own data discovery capabilities in 2012, mostly in the image of Tableau's functionality, and are integrating and bundling data discovery capabilities with their BI and analytic platforms for free, or at a low cost, to proactively meet their customers' business user ease-of-use requirements — and, more importantly, to defend their installed bases from the adoption and expansion of Tableau and the other data discovery vendors. This could threaten Tableau's land-and-expand growth strategy, which relies on its adoption as a complementary vendor, and could force it to more quickly enhance its enterprise credentials to continue its rapid growth.
  • Although customers report using Tableau for a broad range of use cases, Tableau's product functionality is more narrowly defined around analysis, interactive visualization and dashboards. It lacks broader BI platform capabilities, such as production reporting. Customers that need capabilities spanning systems of record reporting and interactive dashboards and visualization from a single tool are less likely to choose Tableau.
  • Tableau's product functionality is generally well-received this year; however, a bit of realism has set into its customer functional assessments, with users rating enterprise features such as metadata management, BI development tools and BI infrastructure below the survey average. This suggests that Tableau's enterprise readiness is a work in process.
  • Tableau's partner program, while expanding over last year, still lags behind that of similar vendors (such as QlikTech). However, it continues to make progress (including outside North America) in increasing its resellers and system integrators (such as Deloitte and OEM partners) in the past year. As is not uncommon with a small vendor, Tableau is initially pursuing a horizontal platform strategy, and has not embarked on developing vertical or industry-specific applications, although it has a number of OEM and service partners that create domain and vertical solutions using its platform (for example, for healthcare, manufacturing and K-12 schooling).
  • Tableau has a limited but expanded international presence, with the majority of its customers likely to be larger companies in North America. Tableau has offices in London, Dublin, Singapore and Tokyo, with customers in more than 100 countries. Support comes from London in EMEA, Singapore in Asia/Pacific and Seattle in North America, with continued global sales expansion planned. The software is now available in English, German, French, Spanish, Brazilian Portuguese, Japanese, Chinese and Korean, although support services are primarily available in English with some limited localized support.


  • Targit promotes a vision of BI and analytics that extends from information to action in an organization. It follows the principle of "observe, orient, decide, act," and is supported by an integrated set of features, including prediction-based notifications and guided analytics in conjunction with more traditional BI features. The integration of features offers a means to support more complex analytic needs in organizations that may not have the skills to build out data mining models with other tools, and may speed up their decision-making processes.
  • The company delivers a consistent user experience, integrating components of the BI platform and, thus, reducing the need to move between different tools. Patented capabilities in the product work to customize the environment to fit previous users' preferences, aiding navigation and accelerating time to results. This is surely contributing to the good survey results on ease of use for end users, which is identified as a relevant driver for the adoption of Targit's solutions.
  • The Targit BI platform includes tools that help set up the environment with very little intervention — implementation cost and effort have better results than the average in the survey. The platform does a significant amount of the setup automatically, ranging from scheduled report generation, drill-down and dashboarding to intelligent search, alerting and some level of data mining. As a result, Targit's customer organizations report that development tasks are easier than on average.
  • Targit's customer base continues to be tightly connected to those using Microsoft; 80% of its customers are using Microsoft as their primary ERP software provider — a concentration on a data source that no other vendor is even close to replicating — and 70% are using Microsoft as their primary data warehouse. Being so focused on a specific market segment provides differentiation from competitors, and may be a clear strength in some customer bids, but also makes Targit somewhat vulnerable to Microsoft's strategy for this space.
  • The company's self-service capability is also a strength. In 2012, Targit added Xbone — a new component for user-driven analysis that can be triggered by an action as simple as dragging an Excel spreadsheet to a custom folder on the desktop. The system will interpret the file structure, load it into memory, and suggest and present visualizations.
  • Targit has developed a strong OEM channel — with HP and Microsoft among its resellers — and it is trying to expand its reach outside Northern Europe, where it has enjoyed greater success. The U.S. and Brazil are two countries helping to fulfill this objective. Overall, its sales relationships with customers have been rated above average.
  • While Targit is considered an enterprise standard by most of its customers, it is very much a midsize enterprise BI solution. The solution is used by some of the smaller customers on some of the smallest data volumes, and with smaller-than-average numbers of end users in the survey.
  • Targit customers continue to cite problems with poor performance, with 13% of references reporting an inability to handle data volumes — twice the survey average. The issue may be a limitation for successful deployments, considering that the average data volume for Targit is just 256GB — which is much smaller than the survey average at around 3TB. Customers must take this finding into consideration while evaluating the tool, asking for references comparable to their own deployments. Targit's initiatives to address performance issues, such as in-memory analytics, have yet to impact this assessment, given that Targit Xbone was not in the market until late 2012.
  • References rated Targit below average for most BI functional capabilities. The company achieved above-average or close-to-average ratings in scorecards, development tools and Microsoft Office integration in the survey, but was below average in all other functional capability areas.
  • Targit's customers rated the support they receive as below average, with levels of expertise, response time and time to resolution at or near the bottom quartile. While not the desired result, it's an improvement over last year's rating, and is most likely a result of the company's effort to improve satisfaction by having direct interactions with customers, even if sales are managed through partners. This effort and its consequently upward trend in customer feedback must continue throughout 2013. A more positive result can be achieved by the product quality — which includes reliability and bug-free software — showing results near the top for all vendors in this Magic Quadrant.

Tibco Spotfire

  • Tibco Spotfire is a flexible and easy-to-use platform for business user data discovery and analysis, for authoring analytic applications, for publishing interactive and visual dashboards, and for building predictive models and applications. Tibco Spotfire's interactive visualization capabilities are now enabled by a hybrid, in-memory and newly added direct query access approach to support, and they leverage larger enterprise-managed datasets than previously possible.
  • Tibco Spotfire's strong product vision has been and continues to be a key strength. Its focus on advanced and real-time analytic applications and dashboards delivered to mobile devices contributes to its vision. Unlike the other data discovery platforms (for example, QlikView and Tableau), Tibco Spotfire is leveraging the acquisition of Insightful and its newly released runtime engine for R for data mining, as well as its integration with Tibco middleware, Tibco Software's acquisition of LogLogic, and Tibco Software's social capability, tibbr, to broaden the possible spectrum of end-user-driven interactive analysis and data sources, and to incorporate business events and predictive analytics. In particular, in the latest release of Spotfire, Spotfire 5.0, the product features a commercial, integrated runtime engine for R. This engine can run any R model and will be integrated into other Tibco products, such as LogLogic, which is a competitor to Splunk. In addition to statistician-oriented tools, which allow for maximum flexibility in complex model building, new 5.0 capabilities expose a set of code-free modeling tools to analysts. These have the potential to put more advanced analytics in the hands of a broader set of users, and to enable a seamless analytic model development workflow between business analysts and data scientists. This set of capabilities makes Tibco Spotfire well-positioned to take advantage of the increase in market demand for packaged analytic applications and dashboards, which increasingly feature predictive analytics capabilities to make analytics accessible to nontraditional BI users.
  • Tibco Spotfire is included in the Leaders quadrant for the first time this year because of its strong product vision combined with increased BI market momentum, which is largely driven by higher levels of investment by Tibco in Spotfire marketing, awareness, and sales and partner channels. Momentum for Spotfire has also been driven by Tibco stack positioning, where Spotfire is now prominently positioned as a critical differentiator for the Tibco stack in support of Tibco big data analytics, which is a key market initiative for Tibco. The combination of these 2012 initiatives has resulted in stronger market awareness and an increase in the shortlisting of Tibco Spotfire outside its traditional installed base of niche users.
  • Much like the other data discovery vendors that are addressing increasing market requirements for intuitive, highly interactive BI platforms, Tibco Spotfire's customers are very satisfied with many aspects of the relationship. Customers have a positive view of Tibco Spotfire's future; they report success in terms of expanded usage over the past year and have an above-average view of Spotfire's product quality. The Tibco Spotfire platform also earned above-average performance scores, albeit on smaller-than-average datasets. Over the past year, Tibco Spotfire made investments, which are ongoing, in Tibco Spotfire 5.0 to improve performance on larger and larger datasets with new, direct SQL and MDX query capabilities and an updated, high-performance in-memory data engine.
  • Tibco Spotfire has among the highest complexity of user analysis scores of any vendor in the Magic Quadrant, while at the same time customers rate it above average on ease of use, particularly for end users. Tibco Spotfire customers continue to choose it for its ease of use for end users and functionality more often than they do most other vendors, with above-average ratings for achievements of business benefits. Tibco Spotfire customers report the largest percentage of users of any vendor in the Magic Quadrant using the platform for interactive visualization, and among the highest percentage of users conducting ad hoc query and analysis (simple and complex), and deploying predictive analytics, with above-average functional rates in these three capabilities. Because of Tibco Spotfire's ease of use, more users can leverage the benefits of more advanced analytics. This paradox typifies why data discovery capabilities in general, and Tibco Spotfire in particular, are so compelling for business users, and why they are proliferating.
  • Tibco Spotfire's cloud version of its software allows business users to author and share Tibco Spotfire visualizations and dashboards without having to install the software on-premises. While cloud adoption and intentions are generally low (67% say they will never put their enterprise BI in the cloud) in the survey population at large, Tibco Spotfire has among the highest percentage of customers using (14%) or planning to deploy Spotfire in the cloud in the next 12 months (19%). Spotfire's cloud success over the past two years appears to be coming from deployments by line-of-business users and departments versus IT, where cloud investments have had lower acceptance.
  • Even though the average employee size of a company that uses Tibco Spotfire software is the among the highest in the survey, and although Tibco Spotfire has some customer references with large datasets and thousands of users, on average, its deployments tend to be focused on a department or multiple departments in global companies with below-average data volumes and numbers of users, when compared with those of other vendors. Tibco Spotfire also scored among the lowest of all vendors in the reference survey on the percentage of customers that consider it to be their BI platform standard. The combination of this result with Tibco Spotfire's strong functionality ratings in interactive visualization, ad hoc analysis and predictive analytics suggests that, while it is not usually the enterprise standard, it has been successful in augmenting the BI standard when more flexible discovery-based and sophisticated analysis is required. This complementary position may be under increased threat over time from enterprise vendors that added data discovery features to their platforms in 2012 and are aggressively enhancing them.
  • Tibco Spotfire is well-suited to building analytic content ranging from basic interactive visualizations and dashboards to advanced interactive analytic applications, but the perception of Tibco Spotfire's license cost and packaging continues to be a factor limiting its consideration beyond high-end requirements. As a result, Tibco Spotfire is not included on shortlists as frequently as its primary competitors — QlikTech and Tableau in particular — when basic, mainstream data discovery capabilities are required, even though Spotfire's awareness has increased substantially over the past year. While a premium for Tibco Spotfire software may be justified, given its differentiating features around collaborative, mobile, advanced and real-time analytics, Tibco Spotfire must overcome its high license cost reputation to capitalize on the buying momentum that's driving the growth of more mainstream and competitively priced and packaged data discovery alternatives. This will become increasingly important as the stand-alone data discovery vendors, including Tibco Spotfire, face increased competitive pressures, particularly on pricing, from the enterprise BI platform vendors that have now added data discovery capabilities to their platforms, and are often bundling them without additional license costs as features of their platforms. As further evidence of its high license cost reputation, this year, like the past two years, license cost continues to be cited more frequently than most other vendors in the Magic Quadrant survey as a limitation to broader deployment, and its "total license cost per user" continues to be above the survey average. Moreover, while Tibco Spotfire customers are generally happy with most measures of the customer experience — as reflected in its strong position on the Ability to Execute axis of the Magic Quadrant — the one point of dissatisfaction they have expressed is with the sales experiences, which include presales, sales, contracting and pricing.
  • While Tibco Spotfire is rated highly in the survey for ad hoc analysis, interactive visualization and predictive analytics, it is rated in the bottom third of vendors for static and parameterized reporting, and has scored below the survey average in areas that are related to enterprise readiness, such as BI infrastructure, metadata management and development tools, confirming that its true sweet spot is in providing a flexible, easy-to-use environment for advanced analysis. Much like for the other data discovery vendors, adding enterprise features to support larger data and user adoption requirements to compete against the traditional BI players that have now added data discovery capabilities will be an important competitive requirement in the future.
  • Support scores appear to have suffered this year compared with last year, which could be a casualty of high growth. While level-of-support expertise is rated above average, response times and time to resolution scored below the survey average.

Vendors Added or Dropped

We review and adjust our inclusion criteria for Magic Quadrants and MarketScopes as markets change. As a result of these adjustments, the mix of vendors in any Magic Quadrant or MarketScope may change over time. A vendor appearing in a Magic Quadrant or MarketScope one year and not the next does not necessarily indicate that we have changed our opinion of that vendor. This may be a reflection of a change in the market and, therefore, changed evaluation criteria, or a change of focus by a vendor.


Birst, Bitam, GoodData
Other Vendors to Consider
Even though they did not meet the criteria for inclusion in this Magic Quadrant, the following vendors are making an impact on the BI and analytics platform market:
1010data is a U.S.-based company focused on the delivery of cloud-based analytics in large datasets. Its BI product, marketed as the Trillion-Row Spreadsheet, provides an interface by which users can explore their detailed data using calculations, filters and statistical functions in a familiar spreadsheet format. Users can also use advanced analytics capabilities, such as predictive modeling. The information is usually loaded onto 1010data's cloud-based servers, although there is also an on-premises option, and the product is often able to deliver subsecond response times to queries, even with billions of rows being analyzed.
Advizor Solutions
Advizor is a Bell Labs spinoff, headquartered in Chicago, that specializes in interactive data visualization and predictive modeling. The company provides data discovery through a range of sophisticated visualizations that particularly appeals to advanced users. It also delivers predictive modeling capabilities, an in-memory database, and client tools for the Web and iPad. Regular users can use these capabilities to gain insights consuming highly interactive dashboards, but Advizor's real value will be better perceived by power users doing ad hoc visual analysis — replacing or complementing query and table-based analytics from other tools.
U.S.-based Altosoft offers a BI platform designed to provide rapid, code-free development for reporting, ad hoc analysis, interactive visualization and dashboard applications with high performance through the use of a data integration and analytics engine (MetricsMart) that utilizes server-side distributed in-memory and incremental preprocessing techniques. The majority of Altosoft's growing set of more than 500 customers, particularly those in healthcare and financial services, select the platform because it offers a combination of traditional BI platform and data discovery as well as business process intelligence (discovery and analysis) features, although it also competes primarily in those same markets to address traditional BI requirements. In addition, it competes by promoting its other operational intelligence functions, such as data mapping, real-time metrics, outlier identification, user-defined alerts and incident management features. Shipping product since 2006, Altosoft has developed a number of key OEM partnerships, including OpenText, NTT Data (healthcare) and Albridge (mutual fund). Altosoft's solution also offers a traditional on-premises option and a SaaS-based option, which can be deployed in a hybrid configuration to allow data to be collected and prefiltered behind a customer's firewall, and then use a MetricsMart with dashboards/reports in the cloud. References indicate that they select Altosoft for its product functionality, developer ease of use and data integration capabilities.
Dimensional Insight
Privately held Dimensional Insight, based in Burlington, Massachusetts, was founded in 1989 and has several thousand customers across a range of industries in more than 30 countries. The company offers an end-to-end BI and data integration platform with flexible deployments that include on-premises SaaS and hybrid options. In the U.S., the company has particular success in the healthcare provider and manufacturing and distribution sectors. From our customer survey feedback, Dimensional Insight is rated highly for breadth of functionality, ease of use for the end user, and overall TCO, and slightly below average for ease of use for developers. Dimensional Insight has made significant investments, bolstering its mobile technology and vertical offerings for the healthcare and distribution industries.
eQ Technologic
eQ Technologic, based in Costa Mesa, California, offers eQube, a platform for enterprise software infrastructure. To date, eQube has about 200 worldwide customers in the following industries: aerospace and defense, automotive and machinery, high tech and consumer packaged goods, among others. eQube-based solutions have been predominantly used by eQ customers in the product life cycle management (PLM) domain. eQ sells through its partnership with Siemens PLM Software, as well as directly to the end customers by offering comprehensive solutions that use one or more of eQube's offerings. Based on feedback from a limited number of customers, eQube-BI is primarily used for rapid and dynamic BI capabilities, including dynamic metrics, dashboards, and detailed analysis reporting out of PLM, ERP and other key systems. The major reasons why eQ's customers select eQube are due to its rapid and agile ability to connect with enterprise applications (for read and write) natively, and also its ability to offer a set of solutions that individually and/or collectively address core business issues, such as BI in PLM, organizationwide BI (in-memory analytics leading to big data analytics), application synchronization for migration, data quality assessment/repair, and enterprise integration bus for master data management.
InetSoft is headquartered in the U.S. It is a dashboard and reporting vendor with more than 3,000 clients in many geographies, and it has support centers in the U.S. and China. The company sells directly as well as through more than 250 OEMs. In addition to a paid version of its software, the company also makes available a free download for evaluation and individual use. This year, InetSoft references reported that the size of users and data volumes were much higher than last year — around 2,000 and 2.2TB, respectively. In 2012, InetSoft's major improvements included expanded data source support for Google Analytics, AdWords, and integration with Microsoft SharePoint and Google Maps. InetSoft also added broader support for mobile devices using HTML5. Companies select InetSoft for functionality, ease of use for developers and end users, and TCO.
U.S.-based JackBe delivers real-time BI product capabilities through its Presto product line. The firm is very clear about its real-time BI mission, and provides integration and mashup functions that are deployed in operational intelligence scenarios. Clients create applications such as real-time data center monitoring, sales and service performance, and program management — which are often integrated within a portal or mobile application. The limited references in this year's survey reported exceptionally broad deployments in the thousands of users. JackBe customers selected the product for its data access and integration capabilities, its development ease of use, and its strengths in information infrastructure integration, indicating that the products are utilized to develop easy-to-use applications for business users.
Jedox is a German company that delivers integrated BI and performance management capabilities. Although Web and mobile clients are available, Jedox's users will spend most of the time using the product in a familiar environment, such as Excel, where an add-on allows them to import information, execute analysis, perform simulations — including write-back operations — and design their spreadsheet-based reports. This characteristic makes the product a particularly good fit for finance and planning areas, where spreadsheets are still the de facto standard for information analysis and reporting. Hence, Jedox is used by many of its customers as a complementary tool to an existing BI platform, bringing additional control and better data exploration capabilities to plain Excel, while retaining its flexibility. Jedox promotes its in-memory OLAP Server database engine, which can use graphics processing units for high-speed planning and reporting purposes.
myDials/Adaptive Planning
Another interesting BI SaaS vendor is myDials. The company was founded in 2006 and delivers myDials Performance Management Platform, a cloud-based, highly interactive data visualization and dashboarding system. The platform features built-in, business-user-oriented statistical capabilities for identifying trends. In 2012, myDials was acquired by Adaptive Planning, a cloud-based CPM and BI solution vendor for midsize companies and large corporations. MyDials gains access to Adaptive Planning's more than 1,500 customers, additional distribution OEMs and worldwide channel partners. In the technical area, myDials was fully integrated with Adaptive Planning before the acquisition. Eight references responded on behalf of myDials and indicated that they selected the product for functionality, ease of use for end users and performance. Feedback was stellar, with very high ratings (either top or second top) for OLAP, scorecard, prescriptive modeling, simulation and optimization, as well as predictive and data mining. Customer and sales experience marks were in the top quartile, too.
Phocas, headquartered in the U.K., is a subscription-based BI platform, positioning its products directly to business users. Defined integration to many major ERP and CRM systems — including Epicor Software, Microsoft Dynamics and Infor — is noted as a specific strength. More than 60% of references indicated that they selected Phocas for its ease of use. However, average deployments of Phocas incorporate less than 100GB of data and around 50 users. The named-user subscription license is term-based (a minimum of six months). Clients rate interactive exploration and analysis of data, and ad hoc query, in the top quartile. With more than 850 customers throughout Europe, Australia and North America, the product is available in major European languages and Chinese.
SpagoBI is a 100% open-source BI platform sponsored by the Engineering Group, an Italian IT consultancy. The Engineering Group uses SpagoBI to build out vertical applications on behalf of customers. In 2012, SpagoBI's major enhancement included a complete revision of architecture and components, a new chart engine, a new worksheet engine, a mobile BI engine and a new designer for development. Eleven SpagoBI references responded to the Magic Quadrant survey, but we can derive some information about the product and its uses. References reported heavy use of report viewing, and doing moderately complex to complex ad hoc analysis and discovery, interactive exploration and collaboration functions. Clients indicate that they select SpagoBI for license cost and implementation costs/efforts, followed by product quality and the sales relationship.
Strategy Companion
Privately held Strategy Companion has focused on delivering Microsoft SQL Server Analysis Services-based BI solutions to its now 1,900 customers since it was founded in Taiwan in 2001. The company has since added support for relational, Excel, Access and xVelocity in-memory data sources. In 2005, the company moved its headquarters to Irvine, California, and also has regional offices in China, Taiwan and the U.K. Analyzer Enterprise provides zero-footprint browser-based reporting, analytics and dashboarding capabilities for internal corporate users. SaaS and OEM offerings are available for external users. Analyzer Mobile supports tablets and smartphones from Apple, Google and RIM mobile ecosystems; it is based on HTML5 and is capable of detecting the mobile device and optimizing the interface accordingly. Data from this survey showed that the number of end users was around one-third of the average. Other capabilities that scored above average were interactive exploration and analysis of data, mobile BI, the ability to reuse existing content for mobile deployment, adoption of the solution as a BI standard, cloud BI, percentage of power users/business users, data volume, use of external data, number of users external to the organization, complexity of analysis, collaboration, Microsoft Office integration, product quality, support expertise, support resolution time and sales expertise. Customers choose Strategy Companion for ease of use for end users and integration with the information infrastructure, overall TCO, license cost, and implementation cost and effort.
Founded in 2003, Yellowfin is a BI vendor that provides an end-to-end BI and data integration platform, and offers cloud and in-house deployment options. Yellowfin has more than 600 customers worldwide. It sells directly, as well as through third-party resellers and more than 150 OEM partnerships, offering a free trial license for evaluation purposes. Yellowfin focuses on the following capabilities: mobile BI delivery, collaboration, location intelligence and embedded BI. With its most recent release, Yellowfin 6.2, the vendor now includes Storyboard, a fully integrated and interactive PowerPoint-like presentation and collaboration module. Yellowfin offers mobile BI for any device via native applications for the iPhone, iPad and Android devices, or the Web browser. Yellowfin content syndication also allows customers to embed fully interactive reports and dashboards into any third-party Web-based application via a YouTube-like JavaScript API. Based on Yellowfin's customer feedback in this survey, the user size and data volume were above average, and users choose Yellowfin for product quality, overall TCO, license cost, plus implementation cost and effort.
Three vendors in particular — Datameer, Karmasphere and Platfora — did not participate in the Magic Quadrant customer reference survey, nor would they have the revenue to be included in this Magic Quadrant. However, the work they are doing as analytical platforms for a Hadoop file system is worthy of consideration for its contribution to the market.



Inclusion and Exclusion Criteria

To be included in the Magic Quadrant, vendors must generate at least $15 million in BI and analytics-related software license revenue annually. Gartner defines "total software revenue" as revenue generated from appliances, new licenses, updates, subscriptions and hosting, technical support, and maintenance. Professional services revenue and hardware revenue are not included in total software revenue (see "Market Share Analysis: Business Intelligence, Analytics and Performance Management, Worldwide, 2011").
Vendors that also supply transactional applications must show that their BI and analytics platforms are used routinely by organizations that do not use their transactional applications.
Vendors must deliver at least 10 of the 15 capabilities detailed in the Market Definition/Description section at the top of this research.
Vendors must be able to obtain a minimum of 30 survey responses from customers that use their platforms.
This year's Magic Quadrant customer survey included vendor-provided references, survey responses from BI and analytic users from Gartner's BI Summit, as well as respondents from last year's survey. There were 1,702 survey responses, with 256 (15%) from non-vendor-supplied reference lists. To ensure the integrity of the survey data, each survey response was checked by company respondent email. For survey responses from nonidentifiable email accounts, such as Gmail or Yahoo accounts, the respondent was contacted and had to provide Gartner with a company email address, a company role and other contact information.
Further details of the survey results will be published in forthcoming research.

Evaluation Criteria

Ability to Execute

Vendors are judged on their ability and success in making their vision a market reality. In addition to the opinions of Gartner's analysts, the scores and commentary in this research are based on three sources: customer perceptions of each vendor's strengths and challenges, derived from BI-related inquiries with Gartner; an online survey of vendor customers conducted in late 2012, which yielded 1,702 responses; and a vendor-completed questionnaire about the vendor's BI strategy and operations.
*Product/Service: How competitive and successful in this market are the goods and services offered by the vendor?
Overall Viability: What is the likelihood of the vendor continuing to invest in products and services for its customers? Viability includes an assessment of the overall organization's financial health, the financial and practical success of the business unit, and the likelihood of the individual business unit to continue to invest in the product, continue to offer the product and continue to advance the state of the art within the organization's portfolio of products.
*Sales Execution/Pricing: Does the vendor provide cost-effective licensing and maintenance options? This covers the technology provider's capabilities in all presales activities and the structure that supports them. This also includes deal management, pricing and negotiation, presales support and the overall effectiveness of the sales channel.
Market Responsiveness and Track Record: Can the vendor respond to changes in market direction as customer requirements evolve? This covers the ability to respond, change direction, be flexible and achieve competitive success as opportunities develop, competitors act, customer needs evolve and market dynamics change.
*Customer Experience: How well does the vendor support its customers? How trouble-free is the software?
*These criteria are scored in part or directly from input from the Magic Quadrant customer survey.
Table 1. Ability to Execute Evaluation Criteria
Evaluation Criteria
Overall Viability (Business Unit, Financial, Strategy, Organization)
Sales Execution/Pricing
Market Responsiveness and Track Record
Marketing Execution
No Rating
Customer Experience
No Rating
Source: Gartner (February 2013)

Completeness of Vision

Vendors are rated on their understanding of how market forces can be exploited to create value for customers and opportunity for themselves. Like the Ability to Execute criteria, in addition to Gartner analysts' opinions, the Completeness of Vision scores and commentary in this research are based on three sources: customer perceptions of each vendor's strengths and challenges, derived from BI-related inquiries with Gartner; an online survey of vendor customers conducted in October 2012, which yielded 1,702 responses; and a vendor-completed questionnaire about the vendor's BI strategy and operations.
When determining Completeness of Vision for the Offering (Product) Strategy criterion, Gartner evaluated key trends that will drive business value:
Decision Optimization: Capabilities that deliver insights on real-time information and events, recommend optimal courses of action, and capture and facilitate decision collaboration will optimize decisions and performance outcomes. These capabilities include real-time prescriptive analytics, such as simulation, forecasting and optimization, embedding analytics and business rules in repeatable and structured decision processes, as well as the integration of collaboration and social capabilities with analytics.
Consumerization: The demand for easy-to-use tools has already fueled tremendous growth in data discovery and mobile BI. We see the trend to "make hard things simple" continuing, with greater investments in business-analyst-oriented predictive and prescriptive analytics tools and applications, natural language processing query and analysis (text and voice), geospatial and 3D analytics, and advanced mobile analytics.
Big Data: The ability to find patterns, correlations and insights across multistructured data will become a mainstream requirement as companies try to better innovate and find operational efficiencies across business processes that leverage data. These include capabilities that enable the collection, storage, management, correlation, organization, exploration and analysis of multistructured data.
Existing and planned products and functionality that enable these trends factor into each vendor's product vision score.
*Market Understanding: Does the vendor have the ability to understand buyers' needs, and to translate those needs into products and services?
Marketing Strategy: Does the vendor have a clear set of messages that communicate its value and differentiation in the market?
Sales Strategy: Does the vendor have the right combination of direct and indirect resources to extend its market reach?
Offering (Product) Strategy: Does the vendor's approach to product development and delivery emphasize differentiation and functionality that map to current and future requirements?
Vertical/Industry Strategy: How well can the vendor meet the needs of various industries, such as financial services, manufacturing or retail?
Geographic Strategy: How well can the vendor meet the needs of locations outside its native country, directly or through partners?
*This criterion is scored in part or directly from input from the Magic Quadrant customer survey.
Table 2. Completeness of Vision Evaluation Criteria
Evaluation Criteria
Market Understanding
Marketing Strategy
Sales Strategy
Offering (Product) Strategy
Business Model
No Rating
Vertical/Industry Strategy
No Rating
Geographic Strategy
Source: Gartner (February 2013)

Quadrant Descriptions


Leaders are vendors that are strong in the breadth and depth of their BI platform capabilities, and can deliver on enterprisewide implementations that support a broad BI strategy. Leaders articulate a business proposition that resonates with buyers, supported by the viability and operational capability to deliver on a global basis. Small vendors such as Tableau, QlikTech and Tibco Spotfire, which may lack strong scores for geographic or vertical strategy, or breadth of capabilities in the offering (product) criterion, are still Leaders due to the strength of their market understanding and marketing strategy. The evidence that they are market leaders comes from the fact that most of the market is trying to imitate the simplicity of their architecture and the ease of use that it provides.


Challengers are well-positioned to succeed in the market. However, they may be limited to specific use cases, technical environments or application domains. Their vision may be hampered by a lack of coordinated strategy across the various products in their platform portfolios, or they may lack the marketing effort, sales channel, geographic presence, industry-specific content and awareness offered by the vendors in the Leaders quadrant. In this Magic Quadrant, two vendors, Birst and LogiXML, were vaulted into the Challengers quadrant this year due to the overwhelmingly positive scores they received on the customer reference survey.


Visionaries are vendors that have a strong vision for delivering a BI platform. They are distinguished by the openness and flexibility of their application architectures, and they offer depth of functionality in the areas they address. However, they may have gaps relating to broader functionality requirements. Visionaries are market thought-leaders and innovators. However, they may still have to achieve sufficient scale — or there may be concerns about their ability to grow and provide consistent execution. There were no Visionaries in the market this year, mainly because most of the Niche Players do not provide the breadth of vision across descriptive, diagnostic, predictive and prescriptive analytics. Some vendors had moderate product breadth, but lacked vision on the other criteria, such as vertical or geographic strategy.

Niche Players

Niche Players do well in a specific segment of the BI platform market — such as reporting or dashboarding — or have a limited capability to innovate or outperform other vendors in the market. They may focus on a specific domain or aspect of BI, but are likely to lack depth of functionality elsewhere. They also may have gaps relating to broader platform functionality. Alternatively, Niche Players may have a reasonably broad BI platform, but have limited implementation and support capabilities or relatively limited customer bases, such as in a specific geography or industry. In addition, they may not yet have achieved the necessary scale to solidify their market positions.


Readers should not use this Magic Quadrant in isolation as a tool for vendor selection. Gartner has defined the BI and analytics market broadly. We are including a variety of products that span a range of buyers and use cases, such as decision management suites, interactive dashboards, and tools that are better for integrated planning. Consider this Magic Quadrant to be more of an executive summary into Gartner's research into this market, and use it in combination with the critical capabilities; customer references survey; strengths, weaknesses, opportunities and threats (SWOTs); and analyst inquiries when making specific tool selection decisions.

Market Overview

Although this is a mature market and has been a top CIO priority for years, there is still a lot of unmet demand. Every company has numerous subject areas — such as HR, marketing, social and so on — that have yet to even start with BI and analytics. The descriptive analytics have largely been completed for most large companies in traditional subject areas, such as finance and sales, but there is still a lot of growth expected for diagnostic, predictive and prescriptive deployments. Moreover, many midsize enterprises have yet to even start their BI and analytic initiatives. Gartner's view is that the market for BI and analytics platforms will remain one of the fastest growing software markets. The compound annual growth rate for the BI and analytics space is expected to be 7% through 2016 (see "Forecast: Enterprise Software Markets, Worldwide, 2011-2016, 4Q12 Update").
In addition, the emerging data-as-a-service trend could significantly grow the market for BI and analytics platforms. Today, the business model is largely "build" driven. Organizations license software capabilities to build analytic applications. However, organizations increasingly will subscribe to industry-specific data services that bundle a narrow set of data with BI and analytic capabilities embedded. This data-as-a-service trend will be driven from well-known, trusted data aggregators, such as Nielsen or Thomson Reuters, as well as industry-specific players, such as IMS (life sciences) or CoreLogic (financial services). In time, most companies — regardless of their business model — will need to provide a data-as-a-service offering (see "Make Customer-Facing Analytics Part of Your Business Model"). Therefore, this data-as-a-service trend has the potential to grow the market significantly as a range of vendors are looking to embed a BI and analytic platform provider's software capabilities into their data-as-a-service offerings.