Gartner Magic Quadrants 2018 for Analytics and Business Intelligence Platforms and Data Science and Machine Learning: Where is IBM positioned?

The Gartner 2018 Magic Quadrant for Analytics and Business Intelligence Platforms as well as for Data Science and Machine Learning was recently issued.

IBM is in the bottom right (“Visionary”) for both Analytics and BI Platforms and for Data Science and Machine Learning* this year.

IBM’s strengths in Analytics and BI Platforms:

  • Augmented and easy to useIBM has been a leader in incorporating augmented analytics or “smart” capabilities into its products(first with Watson Analytics and increasingly with Cognos Analytics) to simplify data preparation, create basic visualizations and perform more advanced predictive analyses.
  • All-in-one platform:The ability to create both reporting and dashboard analytic content in the Cognos Analytics platform is a unique differentiator for IBM in a market that often dictates the requirement of separate tools for standard reporting and more visual/exploratory analysis.
  • Global, socially responsible vendor: IBM has a broad global presence and an ability to support customers in all geographies. It also exemplifies attentiveness to and active participation in social initiatives.
  • Large incumbent user base: Existing Cognos BI customers can upgrade to Cognos Analytics as part of maintenance, so license cost is not a barrier to adoption. Watson Analytics, is a per-user license, but available via digital sign-up. The pricing for its Plus ($30 per user per month) or Professional ($80 per user per month) offerings is lower than for other products with robust augmented analytics capabilities and allows for an easy way to investigate and trial.

Gartner - Magic Quadrant For Analytics and Business platforms


IBM’s strengths in Data Science and Machine Learning:

  • Market understanding: IBM remains a leader in terms of market share, with 9.5% of the data science market.
  • Innovative approach focused on key market trends: With the inclusion of DSX, IBM’s roadmap offers extensive openness, hybrid cloud support and strong analytic capabilities for both expert and novice data scientists across the full analytic pipeline.
  • Data preparation and model management capabilities: IBM SPSS is a trusted and vetted enterprise solution. IBM’s robust data preparation capabilities and ability to operationalize and manage models are key strengths and differentiators.
  • “Legacy” user base across all analytic capabilities: IBM’s strong user base in both the analytics and BI market and the data science and machine-learning market gives it an advantage in terms of not only maintaining usage but extending and increasing it. IBM’s customers tend to exercise due diligence with a view to maintaining or extending their existing investments before considering a move to a different vendor.

MQ data science

*Note that only IBM SPSS Modeler was included in this axis.  Gartner considers Data Science Experience (DSX) and IBM SPSS Modeler as two distinct offerings and that DSX did not meet its criteria for inclusion in the Magic Quadrant as a separate offering.

Note that the report mentions IBM’s DSX offering has potential to inspire a more comprehensive and innovative vision. IBM has announced plans to deliver a new interface for its SPSS products in 2018, one that fully integrates SPSS Modeler into DSX.