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SmartData Collective > Big Data > Data Mining > Overlap in the Business Intelligence / Predictive Analytics Space
Business IntelligenceData MiningPredictive Analytics

Overlap in the Business Intelligence / Predictive Analytics Space

DeanAbbott
DeanAbbott
4 Min Read
Overlap in the Business Intelligence / Predictive Analytics Space
Illustration generated with FLUX.1 [schnell] via Cloudflare Workers AI.
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I’ve received considerable feedback on the post Business Intelligence vs. Business Analytics, which has also caused me to think more about the BI space and its overlap with data mining (DM) / predictive analytics (PA) / business analytics (BA). One place to look for this, of course, is with Gartner, how they define Business Intelligence, and which vendors overlap between these industries. (I think of this in much same way as I do DM; I look to data miners to define themselves and what they do rather than to other industries and how they define data mining.)

I found the Gartner Magic Quadrant for Business Intelligence in 2009 here, and was very curious to understand (1) how they define BI, and which BI players are also big players in the data mining space. Answering the first question, data analysis in the BI world is defined here as comprising four parts: OLAP, visualization, scorecards, and data mining. So DM in this view is a subset of BI.

Second, the key players in the quadrant interestingly contains only a few vendors I would consider to be top data mining vendors: SAS, Oracle, IBM (Cognos), and Microsoft in the “Leaders” category, and Tibco in the visionaries category. Of these, only SAS (with Enterprise Miner) and Microsoft (SQL Server) showed up in the top 10 of the Rexer Analytics 2008 software tool survey, though Tibco showed up in the top 20 (with Tibco Spotfire Miner).

I think this emphasizes again that BI and DM/PA/BA approach analysis differently, even if the end result is the same (a scorecard, dashboard, report, or transactional decisioning system).

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