Quadrants Here, Quadrants There…

While we’re waiting for the Gartner 2018 Magic Quadrant for Data Analytics (should be out any moment), two others related to data analytics were released.

2018 Magic Quadrant for Data Management Solutions for Analytics

This one evaluates “complete software system that supports and manages data in one or more file management systems (usually databases)”. So, think of traditional and cloud-based data warehousing. I’m surprised to see AWS ahead of Microsoft and Oracle in the ability to execute, given that Amazon doesn’t have on-premises offerings (see the ML quadrant below where apparently that’s important).

2018 Magic Quadrant for Data Science and Machine-Learning Platforms

This one evaluates “vendors of data science and machine-learning platforms. These are software products that data scientists use to help them develop and deploy their own data science and machine-learning solutions.” I personally don’t agree with Gartner on the Microsoft Visionary rank, given all the investments Microsoft has made in machine learning.

“Microsoft remains a Visionary. Its position in this regard is attributable to low scores for market responsiveness and product viability, as Azure Machine Learning Studio’s cloud-only nature limits its usability for the many advanced analytic use cases that require an on-premises option.”

Apparently, Azure Machine Learning is not well received as it’s not easy to operationalize. That one I agree with. But “for on-premises workloads, Microsoft offers SQL Server with Machine Learning Services, which was released in September 2017 — after the cutoff date for consideration in this Magic Quadrant.” Not really. In 2016, Microsoft integrated R with SQL Server after the acquisition of Revolution R. Apparently, this wasn’t communicated well to Gartner.