Oracle and the MQ for BI & Analytics 2018

Oracle recognizes self-service data visualization as a critical component of any BI & Analytics regimen, but only part of a broader Cloud-based Data & Analytics Strategy. Gartner sees things slightly differently.

Two years ago I wrote an article about the 2016 release of the Gartner Magic Quadrant for Business Intelligence and Analytics. It was very clear that Oracle and Gartner are not on the same track when it comes to the Analytics market. At that time there were various opinions between the different analysts. Jen Underwood wrote a nice article last year where she explored the results of the 2017 MQ.

Just recently Gartner released the 2018 version of the Magic Quadrant for Business Intelligence and Analytics. Still Oracle and Gartner do not completely agree.

Oracle recognizes self-service data visualization as a critical component of any BI & Analytics regimen, but only part of a broader Cloud-based Data & Analytics Strategy.

Check out why Oracle thinks that the Cloud is a disruptive force for innovation and change with Analytics here. To get a more complete picture of the Analytics market, please check out Forrester Research and BARC, who named Oracle as a Market Leader for Analytics. Also this Ovum publication might be interesting to find out why they think the Cloud is a model for better business.

I still think that there is more than Self-Service when it comes to Analytics. Especially these days with important subjects like the GDPR.

In the end I think you should have a closer look at the the findings of the different analysts. Sometimes a picture says more than a thousand words, but in this case it is important to familiarise yourself with the background.

I would be happy to assist you in this process.

Originally published on LinkedIn.

Author: Daan Bakboord

I am a Self Employed Oracle Data & Analytics Consultant with a great interest in anything closely related to Oracle Big Data Analytics (OBIEE, BICS, OAC, Big Data, Data Integration, Data Visualization, Data Management, Data Architecture).

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