Magic Quadrant for Business Intelligence Platforms

27 January 2011
Rita L. Sallam, James Richardson, John Hagerty, Bill Hostmann

Gartner RAS Core Research Note G00210036


In 2010, business users had greater influence over BI buying, often choosing data discovery vendors as an alternative to traditional BI tools. But megavendors continued to hold the majority of BI market share, despite ongoing customer dissatisfaction, by selling the stack into their installed base.





What You Need to Know



This document was revised on 28 January 2011. For more information, see the Corrections page on gartner.com.

This document presents a global view of Gartner's opinion of the main software vendors that should be considered by organizations seeking to use business intelligence (BI) platforms to develop BI applications. Buyers should evaluate vendors in all four quadrants and not assume that only those in the Leaders quadrant can deliver successful BI implementations. Year-to-year comparisons of vendor positions are not particularly useful given market dynamics (such as emerging competitors, new product road maps, new buying centers) and client concerns/inquiries have changed since our last Magic Quadrant. Therefore, we have evaluated vendors based on these new market dynamics and have reflected the changes in our Magic Quadrant criteria evaluation weights for 2011. For further guidance on the Magic Quadrant evaluation process and on how to use a Magic Quadrant, see "Magic Quadrants and MarketScopes: How Gartner Evaluates Vendors Within a Market." Moreover, while it is tempting for the reader to apply his or her own definitions for the Ability to Execute and Completeness of Vision evaluation criteria in order to judge vendor positions, such assumptions will likely lead to incorrect conclusions. For the purpose of this analysis, Ability to Execute is a function of a vendor's score of five measures that Gartner believes customers care about most in vendor selection. It does not equate to revenue, revenue growth or market share. Completeness of Vision is based on the scoring of six key measures, including, but not exclusive to, "Offering (Product) Strategy." It is important to understand these criteria while judging vendors' positions on the Magic Quadrant. These evaluation criteria are detailed in the Evaluation Criteria section of this document.


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Magic Quadrant



Figure 1. Magic Quadrant for Business Intelligence Platforms



Source: Gartner (January 2011)

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Market Overview
The demand side of the BI platform market in 2010 was defined by an intensified struggle between business users' need for ease of use and flexibility on the one hand, and IT's need for standards and control on the other. With "ease of use" now surpassing "functionality" for the first time as the dominant BI platform buying criterion in research conducted for this report, vocal, demanding and influential business users are increasingly driving BI purchasing decisions, most often choosing easier to use data discovery tools over traditional BI platforms — with or without IT's consent. Yet, despite accelerated data discovery vendor momentum and reports of chronic post-acquisition megavendor customer dissatisfaction, megavendors continue to control the majority share of BI platform market revenue. In particular, some are succeeding at selling into their expansive installed bases by promising major new releases featuring tighter enterprise application process integration, while others are stressing vertical integration within their information infrastructure stacks. At the same time, many independent vendors continue to drive innovation and show resilience with loyal and satisfied customers and fit with heterogeneous processes despite unfounded post-consolidation market speculation of their imminent death. Given market polarization and paradoxes, it is necessary to consider a number of factors now driving the BI platform market and the buying decisions within that market:

Data discovery platform momentum accentuates the need for a portfolio approach. For the past two years, our research in the BI platform market has highlighted a growing bifurcation in terms of buying centers. Specifically, we noted that IT, on the one hand, favors stack centricity, whereas business users and departmental buyers, on the other, often with an enterprise BI standard in place, are increasingly turning to innovative, data discovery tool vendors. These data discovery alternatives to traditional BI platforms offer highly interactive and graphical user interfaces built on in-memory architectures to address business users' unmet ease-of-use and rapid deployment needs. What began as a market buying trend in 2010 has become a fully fledged fragmentation of the market into two distinct segments, as follows:

Traditional enterprise BI platforms:

Key buyers: IT

Main sellers: megavendors, large independents

Approach: top down, IT modeled (semantic layers), query existing repositories

User interface: report/key performance indicator (KPI) dashboard/grid

Use case: monitoring, reporting

Deployment: consultants

Data discovery platforms:

Key buyers: business

Main sellers: small, fast growing independents

Approach: bottom up, business user mapped (mashup), move data into dedicated repository

User interface: visualization

Use case: analysis

Deployment: users

The chasm between these segments has deepened because business users find the benefits of using data discovery tools so compelling that they make this choice despite the risk of creating fragmented silos of data, definitions and tools. This has accentuated the need for IT organizations to back away from a single-minded pursuit of standardization on one vendor to a more pragmatic portfolio approach. Specifically, IT has been challenged to put in place new enterprise information management architectures, development methodologies, and governance processes that accommodate and bridge the gap between the different buying centers, architectures, deployment approaches, and use cases of both segments into an enterprise BI portfolio that can meet both business user and enterprise requirements.

Traditional BI providers slowly embrace the business user challenge. Organizations are rapidly embracing the data discovery value proposition of providing data to end users and empowering them with an ability to model, navigate and visualize data. But traditional BI platform vendors are not sitting still as data discovery platforms capture the hearts, minds and BI spend of their customers. Rather, they are attempting to imitate them with claims of easy-to-use, data discovery alternatives (for example, Microsoft with PowerPivot, SAP with SAP BusinessObjects Explorer, IBM with IBM Cognos Express and Information Builders with WebFocus Visual Discovery), with Microsoft showing the most market traction and promise to date. At the same time, data discovery tool vendors are implementing capabilities to improve their enterprise readiness. Last year, the data discovery platform vendors experienced most of their success at the departmental level with small user (fewer than 350 users) and data (under 200 GB) deployments. In 2010, data discovery tool deployments grew and became more complex. Greater success in the enterprise is the major reason why QlikTech moved into the Leaders quadrant for the first time with larger and more complex deployments (three times the average size of last year). Indeed, the majority of its customers now consider QlikTech as their BI platform standard. This year, traditional BI vendors will accelerate their response to the success of data discovery platforms. This will likely lead to further industry consolidation, which will put pressure on data discovery vendors to continue to improve their enterprise capabilities and to innovate. The market will ultimately coalesce, with future leading vendors from both segments providing ways to bridge the chasm between business users and IT in enterprise deployments. Gartner views "capabilities for integrating departmental and enterprise data models" as one of 10 important capabilities evaluated for the "Offering (Product) Strategy" criterion as part of the "Completeness of Vision" placement (see the Forecast and Completeness of Vision Criteria sections) in this year's Magic Quadrant.

Acquisition transition malaise is the new normal. Customer turmoil from acquisitions typically follows a predictable life cycle. Initially, there is significant customer concern because of uncertainty about product road maps and commitment. This is followed by the actual execution of the acquisition transition in which support, contracting, pricing, sales territory alignments and products are often changed. This transition process takes time and is not easy on customers. At some point, and by definition, successful acquisitions complete the transition and reach a new "normal" for customers, with satisfaction returning to pre-acquisition levels. Unfortunately, this type of transition has not been so smooth in the BI market. Oracle's weaker satisfaction ratings in this year's survey results, along with ongoing dissatisfaction among IBM and SAP customers for the past three years in a row post acquisition, suggests that transition disruption for these vendors may be chronic, and dissatisfaction the new normal. These vendors have new programs in place to improve the customer experience, but they have not yet produced positive results. The varying levels of customer dissatisfaction for these vendors as revealed in the customer survey had a negative affect on their Ability to Execute positions.

Shift from measurement to analysis, forecasting and optimization. Based on Gartner research conducted for this report, reporting and ad hoc analysis remain the dominant styles of information delivery of BI in 2010, but the proportion of respondents reporting their extensive use is down significantly from 2009. At the same time, interactive visualization, predictive analytics, dashboards and online analytical processing (OLAP) usage is increasing, with data discovery platforms also earning the highest ease of use and highest complexity of analysis scores. The increased proliferation of interactive visualization tools, more integrated data mining and packaged analytic applications that encapsulate the complexity of using sophisticated BI analysis tools from business users, are all pushing the power of analysis into the hands of a larger number of users than ever before. Moreover, this data and Gartner inquiries suggest that there is an increasing need for more accurate forecasts and optimized business processes, and to identify leading versus lagging indicators. In response, and challenging the once stronghold lead of SAS, IBM is leveraging its SPSS acquisition, its Cognos BI platform and other IBM technologies, such as content analytics, to deliver packaged analytic applications through its Global Business Services unit. At the same time, many smaller vendors (such as Information Builders, Tibco Software [Spotfire] and MicroStrategy) and most of the megavendors (SAP, IBM and Microsoft) are maturing their capabilities to make statistics, predictive analytic models and forecasting algorithms more consumable in reports, dashboards and analytic applications. We expect this shift to continue as more advanced analysis is encapsulated in easier-to-use tools and applications and is made more accessible to a broader user base beyond the traditional statistician installed base.

Cost as an increasingly important purchasing and portfolio driver. While BI spending grew in 2010, the economic downturn caused an increased focus on cost — research conducted for this report showed that cost was a much higher purchasing driver in 2010 than in 2009. Organizations showed an increased willingness to consider traditional low-cost options such as Microsoft, as well as open source vendors and newer low-priced alternatives from vendors such as LogiXML, for their BI deployments. Another way organizations are managing cost is by offloading basic BI capabilities, such as static reporting, to lower-cost alternatives, or else embedding low-cost BI in purpose-built analytic applications, even when a higher-cost enterprise standard BI tool is in place. This new buying behavior is further accentuating the need for IT to manage a portfolio of tools not only to expand access to functionality not provided by the enterprise standard, but also to lower cost. Because of this increased interest in cost, we added open source vendor Jaspersoft, as well as low-cost vendor LogiXML, to the Magic Quadrant for the first time this year. We expect this buying trend to continue putting downward pressure on price, resulting in vendors being less able to charge and sustain premiums when viable low-cost alternatives exist. Moreover, buyers are showing an interest in alternative niche vendors, data discovery approaches and, to a lesser extent, in alternative deployment models, such as software as a service (SaaS), in order to lower costs or expand functionality. In response, we added niche vendors Salient Management Company, Bitam and Corda Technologies to the Magic Quadrant for the first time. This report also includes commentary on some vendors, which, while not meeting the inclusion criteria for the Magic Quadrant itself, offer a viable alternative for some organizations with specific requirements.

All Niche Players are not created equally. Niche Players in this year's Magic Quadrant have very different functional, geographical or business model specializations and generally fall into three types: (1) Upwardly mobile niche vendors (such as Board International, Targit, newly added LogiXML, Bitam and Jaspersoft) — these vendors are small and may be limited either functionally or geographically, but they are focused on market buying sweet spots, such as ease of use or cost, and therefore have momentum. If they can continue to expand their vision and execute with customers, they are most likely to achieve positive movement in future Magic Quadrants; (2) Solid niche vendors (such as arcplan, newly added Salient and Corda) that have been in the BI market for some time, are focused either functionally, geographically or vertically, and continue to have happy customers in their specific niche. These vendors would need to modify their current product vision and execute on their go-to-market strategies in order to move them beyond their current customer base and make significant movements in future Magic Quadrants; and (3) Fading niche vendors (such as Panorama Software and Actuate), which have strong niche product capabilities, but their customers are progressively losing faith in them as long-term viable vendors. These vendors must make changes both to their vision and execution to remain on the Magic Quadrant in future.

The year 2010 continued to be frustrating for many customers acquired as part of the consolidation frenzy of 2007 and 2008, as they upgraded and expanded BI purchases in line with their enterprise application and information management stacks, despite dissatisfaction. Business users unhappy with the time to deploy and complexity of traditional BI tools exerted growing influence on the BI purchasing decision. They helped drive momentum and acceptance of data discovery tools in a BI portfolio with, or often as an alternative to, traditional BI platforms. Looking forward, 2011 is likely to be a critical year in which ease of use, complexity of analysis, scale and performance, and total cost of ownership will continue to dominate BI market requirements, while the ability to bridge widely proliferating departmental silos with enterprise deployments will be a critical IT and BI vendor challenge. If the global economy continues to inch toward growth through 2011, new opportunities will emerge to build business value. The ability of BI to identify and optimize these opportunities will be under greater pressure than ever to deliver results.

Forecast

Gartner's view is that the market for BI platforms will remain one of the fastest growing software markets despite sluggish economic growth in most regions. Organizations continue to turn to BI as a vital tool for smarter, more agile and efficient business. According to Gartner's annual survey of CIO technology priorities, BI remained among the top five priorities in 2009 (and it was No. 1 in each of the previous four years). That said, however, slow economic growth, increasingly viable low-cost alternatives and consolidation are expected to keep BI platform growth in the single digit range in 2010 and beyond. The BI platform market's compound annual growth rate (CAGR) through 2014 is expected to be 7.0%, while the combined BI, analytics and performance management market's CAGR is expected to be 7.7%.

Three major demand-side factors continue to expand use and drive BI platform revenue growth. Because these factors map to future market requirements, we use them as a scoring rubric to evaluate vendors' Offering/Product and Innovation scores on the Completeness of Vision axis in this year's Magic Quadrant.

Consumerization of BI

BI tools must be simple, mobile and "fun" in order to expand use and value.

Intuitive, fun interfaces: BI business users are demanding the same experience from their BI tools that they have come to enjoy with their personal tools. "I just want a BI tool that's as fast and easy to use as Google" is a common mantra expressed by BI business users when describing their requirements. Like the Apple iPhone and iPad, Google and Facebook, BI tools must be intuitive to use without the need for IT assistance. Ease of use was the No. 1 driver of purchasing in 2010 and will only accelerate as a key requirement in the future. New, iphonesque, intuitive and fun interaction paradigms that are touch enabled, feature visual data movement and are highly graphical and fast will continue to extend more sophisticated and powerful analysis capabilities to a broader set of users.

Mobile: The need for more intuitive and interactive BI tools and applications extends to users on the go, but the vast majority of organizations have yet to embrace mobile BI. But this is set to change very quickly with the proliferation of Apple's iPhone and iPad products, with other tablets on the horizon (an extension of the intuitive interface movement). This represents an inflection point where the portability and presence location features not only enhance the analytic experience, but the larger size and touchscreen and interactivity of the tablet finally make the form factor of mobile devices suitable for BI analysis beyond simple report viewing. Mobile BI has the potential to significantly expand the population of BI users to include a much more mainstream audience.

Business user data mashups: Business user data mashup capabilities accelerate the analytic process and will also extend BI platform use to a broader set of users and use cases. Traditional BI platforms require IT to model data in a well formed semantic layer — this creates a bottleneck with business analysts that want to rapidly and iteratively combine (mashup) and explore data — without relying on IT. Capabilities for tracking the data lineage of how business users combine data and build calculations will create a level of trust in business-user-driven applications and further proliferate their acceptance with other users and IT. Moreover, allowing business users control over how they want to view data also accelerates rapid prototyping and communication, with IT supporting more agile development.

Support for Extreme Data Performance; Emerging Data Sources

Capabilities that enable the analysis of large, volatile and diverse data will open up possibilities for a broad range of new, high-value BI applications and will be another driver of BI growth.

In-memory: In-memory technology is not in and of itself a driver of BI growth, despite the massive hype of many vendors. To drive adoption, in-memory must be coupled with consumer-oriented BI tools, a combination that has been at the heart of data discovery tool success. As they have been to date, in-memory capabilities will continue to be an enabling technology. They will expand BI to a broader range of users, as more and more BI vendors incorporate it into their portfolios to deliver Google-like responses in exploring vast amounts of increasingly diverse data types via intuitive, yet sophisticated and mobile BI tools and applications.

Extreme volumes and nontraditional data types: The volume of information generated from enterprise applications is at an all time high, and growing. And BI applications must increasingly incorporate extreme volumes of diverse data (such as unstructured, Hadoop/NoSQL, social network and device data) that live beyond the confines of an organization's structured corporate data sources, while continuing to meet consumer-oriented response expectations. BI platforms and analytic applications will evolve to support the analysis of the vast amounts of and increasingly diverse and complex data, and data formats with varying latency requirements, to detect patterns and optimize business decisions. Extending customer-facing website applications with BI capabilities that increase revenue or differentiate service will be another positive driver of BI growth. These applications will increasingly incorporate extreme data volumes and nontraditional data, and will support unpredictable demand delivered to a broader range of users both internal and external to the organization. According to research conducted by Gartner, BI platform SaaS and cloud adoption is currently very low, with only around 30% of the current users of BI expecting to adopt either SaaS or cloud in the future. Gartner inquiries suggest that BI SaaS has had the most adoption in specific analytic application areas, such as Web analytics or social media analytics, or embedded as part of other SaaS applications. As data volumes become extreme and must be combined with internal and cloud-based sources, the need for on-demand scalability may change the trajectory of demand and growth for BI platform SaaS and cloud.

Social and content analytics: "Social analytics" is an umbrella term that includes a number of specialized analysis techniques, such as social filtering, social-network analysis, sentiment analysis and social-media analytics. These capabilities are used to measure, analyze and interpret the results of interactions and associations among people, topics and ideas that occur on social-software applications used in the workplace, in internally or externally facing communities, or on the social Web. Content analytics enables users to combine and analyze structured and unstructured data that may or may not be on social network sites. Combining these capabilities with support for extreme data volumes and consumer-oriented tools opens up possibilities for a broad range of new, high-value BI applications and will be another driver of growth.

BI as a Decision Platform

Gartner's user surveys show that "improved decision making" is the key driver of BI purchases. Capabilities that will evolve BI from an information delivery system to a decision platform will increase the value of BI and drive its growth.

BI embedded in the business process: Even though most decisions are made as part of and to optimize a business process, and many must be made in real time based on events, most BI applications today are disconnected from the business process and the decision they support. This will change as the proliferation of embedding BI capabilities in business and analytic processes and packaged analytic applications make BI more actionable at the point of decision. Increasingly including sophisticated role- and industry-specific analysis, predictive and prescriptive capabilities in analytic applications, and encapsulating their complexity from business users will further increase the value of BI, expand adoption and will be another driver of growth.

Unifying BI with planning, simulation, forecasting, prediction and prescription: Leveraging BI into broad performance management initiatives, beyond the office of finance and corporate performance management (CPM) applications, and using it to model complex, often strategic decisions will be another driver of growth. In 2011, this convergence will continue to move beyond basic dashboarding and scorecarding to incorporate predictive analytics and simulation, not only into the planning and forecasting process, but also for predicting what target thresholds should be, for analyzing and prescribing different courses of action (for example, where to build a new plant), and in identifying leading and weak signal indicators. Gartner predicts that, through 2011, organizations that use performance management applications to support a performance-driven culture will outperform their peers by 30%.

Capabilities for unifying departmental data models with enterprise models: One of the challenges with giving business users flexibility over their data and models in a data discovery mode and the expanded use of BI embedded in applications is the proliferation of silos. Capabilities for rapidly integrating business analyst knowledge locked in spreadsheets, black box models and algorithms (often created through business user data mashup capabilities) into corporate data sources and collective intelligence will finally bridge the chasm between the divergent interests of business users and IT. Therefore, it will be a critical driver of BI proliferation and growth. None of the vendors evaluated for this Magic Quadrant fully address this requirement or have credible plans to deliver this critical capability.

Collaborative decision making: Good decision making at all levels of an organization separates high performing companies from poorly performing ones. Yet the vast majority of organizations make thousands of increasingly collaborative decisions, often with a negative or suboptimal affect on performance, without insight into how these decisions are made or their effectiveness. Combining BI applications with collaboration and social software capabilities into collaborative decision-making platforms can alert decision makers to events and changing patterns that indicate an early need to make a decision. It will also enable decision makers to identify and bring together the right people with the right information and decision-making tools to analyze the information, discuss an issue, assess and capture assumptions, brainstorm and evaluate options, and agree on a course of action. BI as part of a collaborative decision-making platform will support higher-quality, more transparent decisions that will increase the value derived from BI applications and drive its growth.


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Market Definition/Description
BI platforms enable users to build applications that help organizations learn and understand their business. Gartner defines a BI platform as a software platform that delivers the 13 capabilities listed below. These capabilities are organized into three categories of functionality: integration, information delivery and analysis. Information delivery is the core focus of most BI projects today, but we are seeing an increase in interest in deployments of analysis to discover new insights, and in integration to implement those insights.

Integration

BI infrastructure — All tools in the platform should use the same security, metadata, administration, portal integration, object model and query engine, and should share the same look and feel.

Metadata management — Not only should all tools leverage the same metadata, but the offering 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 BI platform should provide a set of programmatic development tools and a visual development environment, coupled with a software developer's kit for creating BI applications, for integrating them into a business process, and/or embedding them in another application. The BI platform should also enable developers to build BI applications without coding by using wizard-like components for a graphical assembly process. The development environment should also support Web services in performing common tasks such as scheduling, delivering, administering and managing. In addition, the BI application should assign and track events or tasks allotted to specific users, based on predefined business rules. Often, this capability is delivered by integrating with a separate portal or workflow tool.

Collaboration — This capability enables BI users to share and discuss information and/or manage hierarchies and metrics via discussion threads, chat and annotations, either embedded in the BI platform or through integration with collaboration, analytical master data management (MDM) and social software.

Information Delivery

Reporting — Reporting provides the ability to create formatted and interactive reports (parameterized) with highly scalable distribution and scheduling capabilities. In addition, BI platform vendors should handle a wide array of reporting styles (for example, financial, operational and performance dashboards) and should enable users to access and fully interact with BI content delivered to mobile devices.

Dashboards — This subset of reporting includes the ability to publish formal, Web-based reports with intuitive interactive displays of information, including dials, gauges, sliders, check boxes and traffic lights. These displays indicate the state of the performance metric compared with a goal or target value. Increasingly, dashboards are used to disseminate real-time data from operational applications.

Ad hoc query — This capability 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 allow users to navigate available data sources. These tools should include a disconnected analysis capability that enables users to access BI content and analyze data remotely without being connected to a server-based BI application. In addition, these tools should offer query governance and auditing capabilities to ensure that queries perform well.

Microsoft Office integration — In some cases, BI platforms are used as a middle tier to manage, secure and execute BI tasks, but Microsoft Office (particularly Excel) acts as the BI client. In these cases, it is vital that the BI vendor provides integration with Microsoft Office, including support for document formats, formulas, data "refreshes" and pivot tables. Advanced integration includes cell locking and write-back capabilities.

Search-based BI — This applies a search index to both structured and unstructured data sources and maps them into a classification structure of dimensions and measures (often leveraging the BI semantic layer) that users can easily navigate and explore using a search (Google-like) interface. This capability extends beyond keyword searching of BI platform content and metadata.

Analysis

OLAP — This enables end users to analyze data with extremely fast query and calculation performance, enabling a style of analysis known as "slicing and dicing." Users are (often) able to easily navigate multidimensional drill paths. And they (sometimes) 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 storage architectures, such as relational, multidimensional and in-memory.

Interactive visualization — This gives the ability to display numerous aspects of the data more efficiently by using interactive pictures and charts, instead of rows and columns. Over time, advanced visualization will go beyond just slicing and dicing data to include more process-driven BI projects, allowing all stakeholders to better understand the workflow through a visual representation.

Predictive modeling and data mining — This capability enables organizations to classify categorical variables and to estimate continuous variables using advanced mathematical techniques. BI developers are able to integrate models easily into BI reports, dashboards and analysis.

Scorecards — These take the metrics displayed in a dashboard a step further by applying them to a strategy map that aligns KPIs with a strategic objective. Scorecard metrics should be linked to related reports and information in order to do further analysis. A scorecard implies the use of a performance management methodology such as Six Sigma or a balanced scorecard framework.


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Inclusion and Exclusion Criteria
To be included in the Magic Quadrant, software vendors:

Must generate at least $15 million in BI-related software license revenue* annually.

In the case of those that also supply transactional applications, show that their BI platform is used routinely by organizations that do not use their transactional applications.

Must deliver at least nine out of 13 capabilities detailed in the Market Definition/Description section, above.

Must be able to obtain a minimum of 20 customer survey responses that use the vendor platform as their enterprise BI platform. This is a change from the 30 responses required last year. This change was made to include three vendors, Actuate, Panorama and Jaspersoft, which had fewer than 30 responses, but more than 20, but none-the-less Gartner believes must be included in the Magic Quadrant this year for reasons discussed in each of their respective sections.

* Gartner defines total software revenue as revenue that is 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.

This year's Magic Quadrant customer survey included vendor-provided references, as well as survey responses from BI users in Gartner's BI summit and inquiry lists. There were 1,225 survey responses, with 247 (20%) from nonvendor-supplied reference lists. To ensure the integrity of survey data, each survey response was checked by company respondent e-mail. For survey responses from nonidentifiable e-mail accounts such as Gmail or Yahoo accounts, the respondent was contacted and had to provide Gartner with a company e-mail address, company role and other contact information (this amounted to fewer than five responses, all of which were vetted and ultimately included). Further details of the survey results will be published in upcoming BI platform User Survey reports, looking at how customers rate their BI platform vendors, how vendor customers rate their BI platform functionality and how customers rate their BI platform ownership costs

Note: Pentaho garnered enough survey customer responses for inclusion on the Magic Quadrant, and it indicated to Gartner early in October 2010 that its 2010 BI platform revenue would meet or exceed $15 million. However, Pentaho recently informed Gartner that its growth in BI platform revenue (separate from its stand-alone extraction, transformation and loading [ETL] revenue) was slower than expected and thus represented a much smaller percentage of its overall revenue. This resulted in Pentaho falling well below the survey revenue inclusion requirement of $15 million (this will be reflected in the upcoming 2Q11 report, "Market Share: Business Intelligence, Analytics and Performance Management Software, Worldwide, 2010"). Subsequently, Pentaho was excluded from the Magic Quadrant this year. However, it did provide enough customer references to be included in the Magic Quadrant Customer Survey research notes that will publish in 1Q11.


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Added
Bitam, Corda Technologies, Jaspersoft and Salient Management Company were added to this year's Magic Quadrant, as all were able to meet the inclusion criteria.

Other Vendors to Consider

Even though they did not meet the criteria for inclusion, the following vendors are benefiting from the growth of the BI platforms market and may be worthy of consideration in BI evaluations.

Data Discovery

While three data discovery vendors (QlikTech, Tibco Software [Spotfire] and Tableau) had enough market adoption to earn a spot on the Magic Quadrant itself, there are a number of smaller vendors that could be considered when data discovery is a unique requirement. One of these vendors, Advizor Solutions, provided customer references with enough survey responses to be included in the Magic Quadrant Customer Survey research notes that will publish as complements to this research, but did not meet the revenue requirement to earn a place on the Magic Quadrant in its own right.

Advizor Solutions offers a visually-driven data discovery and analysis tool, with an in-memory performance layer, descriptive and predictive analytics (for which KXEN is the OEM) and a user interface built around a library of sophisticated interactive images. Advizor competes against the likes of Tibco Software (Spotfire) and QlikTech, and arguably predates them. While only a few Advizor references took part in the survey, those that did selected it for its functionality and ease-of-use and rated it highly in its core functional areas (interactive visualization, scorecards, predictive modeling and data mining). In addition, Advizor offers templated solutions for non-profit fundraising, higher education, energy management, healthcare and sales pipeline analysis (salesforce.com). It has a long-standing OEM relationship with Information Builders and with vendors in network security and intrusion, call centers, campaign analytics, and higher education. Despite its time in the market, Advizor lacks the market profile of a number of its "hot" competitors, an issue it needs to address if it's not to lose out in the current data discovery market opportunity "land grab."

Another data discovery tool to consider comes from Lyzasoft. The company's all-in-one BI sandbox empowers business analysts to easily integrate, mashup and analyze disparate data, and create reports and dashboards without IT assistance either on premises or shared via a SaaS model. Lyzasoft includes a columnar storage system built into the desktop application, making it well suited to analytic requirements and giving it the ability to analyze large datasets without the RAM requirements of in-memory solutions, or the row or data size limitations of other desktop BI solutions (such as Excel and Access). Lyzasoft's intuitive graphical environment provides analysts with a sandbox to build up analyses iteratively with an extensive set of out-of-the-box functions and statistics for more complex analysis, and featuring exceptional business user capabilities for tracking lineage of data sources and calculations. What differentiates Lyzasoft from the other data discovery tools is its newly integrated collaborative infrastructure with social software capabilities that allow users within the BI platform itself to search, bookmark, combine, create, tag, share, comment, rate, relate, and interact directly with intelligence content in the form of blogs, microblogs, charts, tables, dashboards and collections of analytic content. It also incorporates Short Message Service (SMS) and e-mail alerting, allowing community members to watch for new publications, comments or updates from people of interest or on topics of interest. Gartner identified Lyzasoft as a Cool Vendor in 2009, a distinction that was well deserved then, and still applies today.

Gartner bifurcates the data discovery tool market into interactive visualization tools and search-based data discovery tools. All the vendors either on the Magic Quadrant itself or listed thus far in this section fall into the former category of vendors. Endeca is one of the unique vendors that falls into the latter. Founded in 1999 as an enterprise search vendor, Endeca is leveraging its search technology and pedigree to renew its focus on the BI platform market. Its new platform, Latitude, combines the simplicity of search with the power of BI by delivering interactive tools that support fast data exploration and discovery on top of its patented hybrid search-analytical database. With its unique platform, there is no need for an overarching data schema — every record and document has its own schema stored in a columnar store with text and data indices built into each column. As a result, the columnar architecture can support in-memory-grade performance without in-memory constraints. The data discovery mode is search-based, which enables navigation and analytics on both structured data and unstructured content, making documents and Web-content part of searchable decision data. Every summary is also a way to query the data, letting users iteratively explore data and ultimately reach conclusions that drive decisions.

SaaS

SaaS is a viable option for some buyers. While only 27% of respondents to the Magic Quadrant survey are currently using or have plans to use SaaS BI and analytics within the next 12 months, the subcategory shows slow but steady momentum as a departmental, mid-market and/or analytic application approach. Customers appreciate a quick time to value, lower upfront costs and the ability to leverage external expertise — business knowledge and/or technical skills — not available in-house. The burgeoning acceptance of cloud computing architectures has also raised the spectre of SaaS BI with many established vendors — Microsoft, SAP, IBM and others — as they look to gain a foothold in this new computing model and as clients evaluate hybrid solutions that may incorporate public and private clouds as well as on-premises and off-premises options. Pure-play vendors such as 1010data, Birst, GoodData, Oco, myDials and PivotLink continue to compete aggressively for mind share and budget dollars. Emerging SaaS BI vendors that have not yet met the revenue criteria for inclusion in this report were also invited to provide customer references for the Magic Quadrant customer survey. Four vendors responded.

Birst, based in San Francisco, provides a SaaS-based end-to-end BI and data integration platform. It also supplies predefined analytic application templates for sales, marketing, finance, supply chain and other functional areas of an organization. The company has developed connectors specifically for salesforce.com and other SaaS-based applications in today's market. It provides customers with the option of either uploading data to Birst or leaving data locally, with only the analysis happening in the cloud. While the company's customer base spans enterprises of all sizes, Birst focuses on serving small and midsize businesses across a wide range of industries. Reference customers indicated they chose Birst for three main reasons: ease of use, implementation costs/effort, and overall total cost of ownership. While references were mostly favorable, customers did indicate that product quality was a worry and that concern about developer ease of use was the primary blocking factor for broader deployment. Customers were very optimistic about Birst's future, with none planning to switch vendors in the next five years.

In contrast, Waltham, MA-based Oco delivers a SaaS-based analytic application deployment platform targeted at consumer goods, industrial products, distribution and logistics, and business services sectors. Clients do not build their own analysis, but rather work with Oco during an eight to 12 week implementation period to capture required data, configure analytic dashboards and reports of an analytic application, and deliver specific content to targeted business users within the organization. The company has designed an innovative data model that supports standard analysis for supply chain, sales, marketing, customer and finance operations, but will also work with clients to build out customized analytic applications tailored to their needs. The Oco product is used to augment installed BI capabilities already in place. In an attempt to provide rapid BI analysis for SAP customers, the company has introduced a new product, Data Exporter for SAP, that extracts needed content from SAP's ERP and/or CRM package and loads it into the Oco data model. The company also resells SAP BusinessObjects BI OnDemand software when the client expresses a desire to extend BusinessObjects BI throughout the organization. Reference customers indicate that Oco is used as a departmental solution, and they highly value the product's ease of use, installation cost and effort model, and its ability to integrate with enterprise applications.

PivotLink, based in San Francisco and with significant development capacity in Seattle, is focused on two areas: building out specific analytic applications and providing its SaaS BI platform for its target customers. At its core, the analytic platform uses a proprietary columnar data structure, allowing granular data to be stored to support extensive analysis of KPIs. Information is sourced from the client on a timed basis (based on customer need). In 2010, the company introduced ReadiMetrix, a series of predefined metrics, KPIs and customizable reports for the retail sector, as well as sales, online marketing and HR functions across a broader swath of industries. PivotLink also recognizes that its SaaS BI and analytics system is part of a broader information ecosystem and has developed an open platform integration strategy that will allow its clients to access data now stored in its system and combine it with other data in the enterprise for combined analysis and reporting. PivotLink references select the software for four main reasons: ease of use, data access and integration, implementation costs and efforts, and system performance. Overall, customers rate PivotLink above average in support and product quality.

Another interesting BI SaaS vendor is myDials. The company was founded in 2006 and delivers Web-based, easy-to use, highly interactive dashboards via a SaaS model. The platform features built-in business user-oriented statistical capabilities for identifying trends, forecasts with error ranges, and patterns with support for drilling into the data while context is maintained to identify the root cause of a problem. Moreover, users can perform real-time what-if analysis to determine the impact of various scenarios, while alerts are shown based on variance from goals or best practice. Its warehouse-in-a-cloud approach supports continuous updates and data synchronization. Fast time to deployment is supported through a set of standard connectors to ERP, CRM, databases, spreadsheets and so on, and libraries of a super set of all the functional areas an organization might need — users can easily add or subtract what dashboards or dials best meet their needs, while designing a completely new dial using a point and click paradigm. In 2010, myDials introduced a packaged application module for marketing executives. It delivers role-based marketing metrics and allows for the integration and automatic extraction of external data from sources such as Google Analytics, Google AdWords and social network sites Twitter and Facebook with internal ERP and general ledger data sources for an end-to-end view of the marketing process, activities and effectiveness. Even though myDials is a relatively obscure SaaS company compared to the other more well known SaaS vendors mentioned in this section, it was able to garner a similar number of responses with overwhelmingly positive customer feedback across most measures in the survey.

Departmental, Workgroup and Midmarket BI

A number of departmental, workgroup and midmarket BI vendors have gained market traction, but do not have the same market awareness as the usual BI market contenders. One such company, with a long history, is Dimensional Insight.

Privately-held Dimensional Insight, based in Burlington, MA, was founded in 1989, and has more than 2,600 clients in over 30 countries. In its lifetime of over 20 years, the company has been quietly but steadily growing its customer base, largely through personal referrals with an end-to-end BI and data integration platform. While most customers use the software in a traditional on-premises installation, the company offers flexible deployment models that also include SaaS and hybrid options. The Diver product suite provides customers and prospects with both Windows- and Web-based user interfaces as well as mobile BI capabilities. Although the suite is used across a wide array of industries, Dimensional Insight has had particular success in the healthcare provider sector. Several clients use the software to better manage operations through staffing and utilization analysis. The product is often used for clinical analysis, especially when reporting on medical care quality metrics and measuring outcomes for external reporting to regulators and local communities.

Statistical and Predictive Analytics

Advanced analysis leveraging statistical and predictive analytics capabilities is an increasingly important requirement in BI applications. However, two major barriers — cost and ease of use of tools — have inhibited adoption to date. Cost is an issue both in terms of software licenses of current market leader SAS, as well as cost of the high-end skills that are typically required for developing prediction models and advanced analytic applications. The difficulty in using existing tools is the second major inhibitor to broader adoption. The three vendors included in this section, while not meeting the Magic Quadrant inclusion criteria, are addressing these barriers. Quiterian provided enough customer references to be included in the Magic Quadrant Customer Survey research notes that will publish in 1Q11.

Quiterian and its Dynamic Data Web (DDWeb) product were only introduced to Gartner in 2010, but have been available in Spain since 2003, where the company has a good presence and reference base — 28 of its customers took part in the survey for this Magic Quadrant. Effectively a large-scale data discovery offering, its core value proposition is easing the use of data mining and statistical analysis, and thus making these capabilities more broadly available. This is something that’s evidently needed — only 11% of firms surveyed for this Magic Quadrant use these functions extensively today. However, this means it’ll be up against some stiff competition, notably from IBM and SAS, as well as from Tibco Software (Spotfire), which offers a similar value proposition for complex data discovery and advanced analytics. Technically, DDWeb uses an intermediate processing layer on top of a columnar database (historically Alterian, but soon its own C-store) to BI functionality (for example, predictive analysis). Quiterian intends to expand its geographical reach quickly, having opened offices in Portugal, Mexico and the U.S. in 2010, as well as through a growing international value-added reseller channel.

Revolution Analytics (founded in 2007 as Revolution Computing and re-launched in May 2010 as Revolution Analytics) has defined a product road map to make open source capabilities for statistical analysis, based on the R programming language and runtime engine, more scalable and accessible to business analysts. Industry veterans in statistical software such as Norman Nie (one of the founders of SPSS) and Robert Gentleman (co-developer of R) lead the company. The company has created add-on components for the R runtime engine to exploit low-cost multicore and multhreaded processing power to speed up the analysis of very large datasets. The company is also working on adding a much-needed graphical user interface to the R engine, which should be delivered in the middle of 2011. Partnerships with other open source vendors such as Jaspersoft and Cloudera will help raise awareness of Revolution Analytics in the market, but the company will face strong competition from incumbent commercial vendors of statistical analysis products and services such as IBM and SAS.

KXEN was founded in 1998 and has been primarily focused on providing solutions for simplifying the development of predictive models for customer life cycle and supply chain analytics. KXEN has over 400 customers. The company's analytic framework is primarily distributed through direct sales, although it has partnerships with leading data warehouse vendors, system integrators, application vendors and OEMs. In 2010, John Ball (previously with salesforce.com and BusinessObjects) joined the company as CEO and the company raised a fourth round of venture financing to carry out further market and international development. In 2010, a new VP of Marketing also joined the company from salesforce.com. John Ball's experience with semantic layers at BusinessObjects appears to be reflected in KXEN's newly announced "semantic layer," made up of the company's Analytical Data Management and Modeling Factory. It will be interesting to see if and how the company expands into cloud-based offerings given the salesforce.com experience of several of its executives.

Open Source

Given the increased interest in lowering cost expressed by customers in our survey, and the open source vendor marketing about numbers of customers and growth, we expected both of the most well known open source vendors, Jaspersoft and Pentaho, to meet the Magic Quadrant inclusion criteria this year. As outlined earlier in the Inclusion and Exclusion Criteria section, Pentaho garnered enough survey customer responses for inclusion on the Magic Quadrant, and it indicated to Gartner early in October 2010 that its 2010 BI platform revenue would meet or exceed $15 million. However, Pentaho subsequently informed Gartner that its BI platform revenue (separate from its stand-alone ETL revenue) was a smaller percentage of its overall revenue than expected. This resulted in Pentaho earning lower BI platform revenue in 2010 than initially represented to Gartner, well below the survey revenue inclusion requirement of $15 million (this will be reflected in the upcoming 2Q11 report, "Market Share: Business Intelligence, Analytics and Performance Management Software, Worldwide, 2010"). As a result, Pentaho was excluded from the Magic Quadrant this year. However, it did provide enough customer references to be included in the Magic Quadrant Customer Survey research notes that will publish in 1Q11.

Even though Pentaho failed to meet all the criteria, it is still a company worthy of note. It provides an open source BI platform made up of ETL, OLAP, reporting and dashboarding, ad hoc analysis, and data mining components all managed from a central BI server deployed either on premises or in the cloud. Low license cost is a key element of Pentaho's value proposition. While open source vendors, including Pentaho, tend to invest more heavily in imitating the core BI functionality of commercial competitors rather than in innovation, Pentaho does have focused areas of forward looking investment, on which it has been able to quickly deliver. In particular, it has integrated a data mining project into its BI platform, it delivered ad hoc reporting for the Apple iPad (in May 2010), and it has been one of the first BI vendors to deliver capabilities for integrating its ETL and BI tools with Hadoop to support large and emerging data sources (in October 2010).

However, according to our survey data, integration of the platform, product functionality and support appear to be concerns for Pentaho customers. Although Pentaho markets a single unified platform managed from a single server, the repositories and authoring environments remain separate with migration to a single repository under way. Pentaho customers rate its BI platform integration lower than any vendor in the survey. To begin to address this issue, the company released its Agile BI capability in March 2010, which includes a single environment for dimensional modeling, data mart building, ETL and OLAP model generation. Pentaho also earned the lowest aggregate product capability score in the survey with below average results across all 13 BI capabilities, which is an indication that functional gaps in the platform remain. Moreover, it earned among the lowest ease of use scores both for developers and end users in the survey, which suggests that it has yet to deliver tools that meet growing requirements for business users to intuitively analyze their data. Given Pentaho's subscription-based model hinges on providing superior support, low scores on all aspects of product support including level of expertise, response time and time to resolution are a concern, particularly since the company's product is also rated below average on product quality, which tends to result in more customer interaction with support. While Pentaho has some very large references, its deployments are primarily departmental. The deployments are roughly half the size of the survey average in terms of number of end users and data volumes, while a majority of its customers do not consider it their BI standard and indicate other vendors as their standards.


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Dropped
No vendors were dropped from this year's Magic Quadrant.


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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 document 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 2010, yielding 1,225 responses; and a vendor-completed questionnaire about the vendor's BI strategy and operations.

Product/Service:* How competitive and successful are the goods and services offered by the vendor in this market? This includes current product/service capabilities, quality, feature sets and skills, whether offered natively or through OEM agreements/partnerships.

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 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 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. This criterion also considers the provider's history of responsiveness.

Market Execution: Are customers aware of the vendor's offerings in the market? This assesses the clarity, quality, creativity and efficacy of programs designed to deliver the organization's message in order to influence the market, promote the brand and business, increase awareness of the products and establish a positive identification with the product/brand and organization in the minds of buyers. This mind share can be driven by a combination of publicity, promotional, thought leadership, word-of-mouth and sales activities. This criterion was not rated separately this year and therefore was given a "no rating" in the Magic Quadrant model. Instead, our assessment of Market Execution was combined with Market Responsiveness and Track Record into one criterion on this year's Magic Quadrant.

Customer Experience:* How well does the vendor support its customers? How trouble free is the software?

Operations: What is the ability of the organization to meet its goals and commitments? This criterion was given a "no rating." Assessment of a vendor's ability to meet its goals and commitments is incorporated into the Market Responsiveness and Track Record criterion.

* These criteria are scored either in part or directly from input from the Magic Quadrant customer survey.


Table 1. Ability to Execute Evaluation Criteria

Evaluation Criteria
Weighting
Product/Service
high
Overall Viability (Business Unit, Financial, Strategy, Organization)
high
Sales Execution/Pricing
high
Market Responsiveness and Track Record
standard
Marketing Execution
no rating
Customer Experience
high
Operations
no rating

Source: Gartner (January 2011)



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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 document 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 2010, yielding 1,225 responses; and a vendor-completed questionnaire about the vendor's BI strategy and operations.

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 maps to current and future requirements? The major BI market growth drivers described in the Forecast section of this report were used as a rubric to assess both the Offering (Product) Strategy and Innovation criteria, which are combined into one score this year.

Business Model: How sound and logical is the vendor's underlying business proposition? Note that this criterion has been given a "no rating" because all vendors in the market have a viable business model.

Vertical/Industry Strategy: How well can the vendor meet the needs of various industries, such as financial services or the retail industry?

Innovation: How well does the vendor direct related, complementary and synergistic layouts of resources, expertise or capital for investment, consolidation, defensive or pre-emptive purposes? How well does the vendor exploit current or new technologies and combine them in a novel way to address a market need? Innovation and Offering (Product) Strategy are combined into one score for the purpose of this year's Magic Quadrant.

Geographic Strategy: How well can the vendor meet the needs of locations outside its native country, either directly or through partners?

* These criteria are scored either in part or directly from input from the Magic Quadrant customer survey.


Table 2. Completeness of Vision Evaluation Criteria

Evaluation Criteria
Weighting
Market Understanding
high
Marketing Strategy
high
Sales Strategy
high
Offering (Product) Strategy
high
Business Model
no rating
Vertical/Industry Strategy
standard
Innovation
no rating
Geographic Strategy
standard

Source: Gartner (January 2011)



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Leaders
Leaders are vendors that are reasonably 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.


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Challengers
Challengers offer a good breadth of BI platform functionality and 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 BI platform portfolio, or they may lack the sales channel, geographic presence and industry-specific content offered by the vendors in the Leaders quadrant.


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Visionaries
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, but they may have gaps relating to broader functionality requirements. A Visionary is a market thought-leader and innovator. However, it may have yet to achieve sufficient scale — or there may be concerns about its ability to grow and provide consistent execution.


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Niche Players
Niche Players are those that do well in a specific segment of the BI platform market — such as reporting — or that have 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. Or they may have gaps relating to broader BI 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. Or they may not yet have achieved the necessary scale to solidify their market positions.


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