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TDWI Upside - Where Data Means Business

Doling Out Bragging Rights for Advanced Analytics

SAS, IBM, KNIME, RapidMiner, and Microsoft posted strong showings in Gartner’s February 2016 Magic Quadrant for Advanced Analytics Platforms report, though Microsoft fell short of market leadership.

In February 2016, Gartner published the latest version of its “Magic Quadrant for Advanced Analytics Platforms” report. Why should you care about Gartner and its many and varied Magic Quadrant reports? Like it or not, Gartner has enormous influence in terms of its capacity to shape enterprise buying habits and determine which vendors can credibly claim to play in specific markets. (

Of the vendors Gartner has determined can credibly play in the market for advanced analytics products and services, SAS and IBM lead the pack, finishing first and second respectively, overall, in the “leaders” quadrant of the report. (SAS has long been an advanced analytics powerhouse; IBM vaulted into contention with its 2009 acquisition of the former SPSS.) SAS and IBM slightly trailed KNIME and RapidMiner on the report’s x-axis, which purports to measure “completeness of vision.” On the y-axis, which aims to measure “ability to execute,” SAS and IBM outstripped KNIME, RapidMiner, and Dell.

All told, Gartner’s report assesses 16 products or services, including offerings from Alteryx (a darling of the self-service data-prep market), Microsoft, Predixion Software, Alpine Data Labs, SAP, Angoss Software, FICO, Lavastorm Analytics, Megaputer Intelligence, Prognoz, and Accenture.

The strong showing of SAS and IBM was basically a foregone conclusion, but several results stood out. First, there was the robust performance of KNIME, or the Konstanz Information Miner, an open source offering freely available under the GNU General Public License. Parent company AG also markets a commercial version that bundles enterprise-oriented collaborative and productivity extensions. KNIME is not a newcomer to Magic Quadrant reports; Gartner listed it as a “leader” in 2015, although in that report, KNIME, along with RapidMiner, trailed SAS and IBM on both axes of the quadrant. This year, however, KNIME and RapidMiner outstripped SAS and IBM on the x-axis.

The 2016 report gives KNIME high marks for its flexibility, ease of integration with third-party tools, and (how else to put this?) open source moxie: “Almost every KNIME customer mentions the platform's flexibility, openness, and ease of integration with other tools. Similar to last year, KNIME continues to receive among the highest customer satisfaction ratings in this Magic Quadrant.” Customers also cited KNIME's excellent cost-benefit ratio in the report, which notes that “its customer reference ratings are among the highest for good value.”

What's not to like? Well, KNIME's not-so-sexy graphical user interface (GUI) and not-so-interactive user experience, for starters. “The most common customer complaints are about the outdated UI,” the report states, noting that KNIME 3.0, which appeared late last year, is said to boast an improved GUI. Customers also expressed “a desire for better performing algorithms for a distributed big data environment.” Finally, customers dinged KNIME for its lack of interactive visualizations, which, according to the report, must be obtained from “data visualization vendors such as Tableau, Qlik, or TIBCO Spotfire.”

RapidMiner, another open source offering, finished just behind KNIME on the x-axis of the Magic Quadrant. As noted above, RapidMiner also improved its year-over-year showing in Gartner’s tally, and thanks to a recent sales and marketing push, it's seeing increased uptake in the marketplace. “RapidMiner received high scores for innovative features such as its 'Wisdom of Crowds' guidance for recommended next steps, and its collaboration features,” the report states, noting that RapidMiner's 2014 acquisition of Radoop—which provides technology designed to simplify the process of building data analytics workflows for Hadoop—has also “contributed to a much more balanced offering.” In addition, “RapidMiner's customers consistently mention the combination of ease of use, with improved productivity from modeling through deployment, and great extensibility,” according to the report.

Finally, Microsoft’s performance is especially intriguing. After all, it finished first on the x-axis (“completeness of vision”) and, relative to 2015, significantly improved its placement on the y-axis (“ability to execute”). Nevertheless, Microsoft remains stuck in Gartner’s “visionaries” quadrant. Why?

Microsoft has a many-pronged advanced analytics strategy. It delivers data mining and statistical analysis capabilities via its SQL Server Analysis Services (SSAS); offers a machine learning (ML) API via its Azure ML (AML) service; and, as of October 2015, offers its Azure-based Cortana Analytics Suite. Microsoft has steadily added to SSAS’s analytics feature set since its introduction in SQL Server 7.0. AML, for its part, has been available for a little over a year. Cortana, a massively integrated cloud analytics platform, consolidates several services—including Azure Event Hub, Azure Stream Analytics, Azure Data Factory, Azure Catalog, Azure Data Lake, Azure SQL Data Warehouse, Azure HDInsight, PowerBI, and Cortana itself—into a single service offering.

Try as you might, you can't deny Microsoft has completeness of vision. Gartner concedes as much, noting that “Microsoft received the highest scores on Completeness of Vision for this Magic Quadrant [and] the Cortana Analytics Gallery is the best example of an analytics cloud marketplace, with an extensive partner ecosystem. Microsoft also has the highest percentage of customers who chose it for its product road map and future vision.”

The report continues its positive assessment of Microsoft with distinctions that would have been inconceivable a decade ago: “Customer references value the strong integration with open source, most notably Python and R, and Microsoft's support for open source communities.”

What's not to like? There's the obvious—namely, that in spite of AML’s strengths and the fact that Gartner gave Microsoft's machine learning service high marks for integrating easily with cloud data sources, some customers won't want to shift their data or their data-processing workloads to the cloud. “Some reference customers cited 'cloud only' as a limitation, which may explain why Gartner has observed only limited market traction for AML to date,” the report concludes.

In a sense, the report implies, Microsoft is getting dinged because of the backwardness of its customers: “Reference customers revealed below-average customer satisfaction. However, most are still using traditional analytics tools—such as SSAS—rather than Microsoft's other offerings.”

About the Author

Stephen Swoyer is a technology writer with 20 years of experience. His writing has focused on business intelligence, data warehousing, and analytics for almost 15 years. Swoyer has an abiding interest in tech, but he’s particularly intrigued by the thorny people and process problems technology vendors never, ever want to talk about. You can contact him at

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