Gartner 2019 Magic Quadrant for Data Science and Machine Learning Platforms

“Expert data scientists prefer to code data science models in Python or R, or to build and run data models in notebooks. Other users are most comfortable building models by using a point-and-click UI to create visual pipelines. Hype about AI is at its peak, but AI must be distinguished from data science and ML. Of course, data science is a core discipline for the development of AI, and ML is a core enabler of AI, but this is not the whole story. ML is about creating and training models; AI is about using those models to infer conclusions under certain conditions.”

Gartner define a data science platform as:

A cohesive software application that offers a mixture of basic building blocks essential for creating all kinds of data science solution, and for incorporating those solutions into business processes, surrounding infrastructure and products.

Knime, RapidMiner, Tibco Software (acquired… Statistica and Alpine Data) and SAS are the leaders in "Magic Quadrant for Data Science and Machine Learning Platforms 2019", check out Alteryx and DataIku.. Open Source based Anaconda, Conda libraries..

Gartner’s 2019 Magic Quadrant for Data Management Solutions for Analytics

Disruption slows as cloud and non-relational technology take their place beside traditional approaches, the leaders extend their lead, and distributed data approaches solidify their place as a best practice for DMSA (Data Management Solutions for Analytics).

Gartner defines a data management solution for analytics (DMSA) as a complete software system that supports and manages data in one or many file management systems, most commonly a database or multiple databases. These management systems include specific optimization strategies designed for supporting analytical processing — including, but not limited to, relational processing, non-relational processing (such as graph processing), and machine learning or programming languages such as Python or R. Data is not necessarily stored in a relational structure, and can use multiple data models — relational, XML, JavaScript Object Notation (JSON), key-value, graph, geospatial and others.

Oracle, Microsoft-Azure, Amazon-AWS, SAP, Teradata, Snowflake, Google-GCP and IBM (blue suite) are the leaders in “Magic Quadrant for Data Management Solutions for Analytics”. Check out for the Niche Player category..

The Forrester Wave™: Enterprise Insight Platforms, Q1 2019

Enterprise insight platforms help CIOs address the continual business demand to go faster in the face of technology complexity.
Forrester defines an enterprise insight platform as: An integrated set of data management, analytics, and development tools that provide a general, enterprise-class platform for building systems of insight.

Forrester's research uncovered a market in which IBM, Microsoft, and SAS are Leaders; Google, SAP, TIBCO Software, and GoodData are Strong Performers; Reltio is a Contender; and EdgeVerve is a Challenger in "The Forrester Wave™: Enterprise Insight Platforms, Q1 2019"

The Forrester Wave™ Strategic iPaaS And Hybrid Integration Platforms, Q1 2019

Forrester’s research uncovered a market in which TIBCO Software, Workato, Dell Boomi, Software AG, MuleSoft, and SnapLogic are Leaders; Liaison Technologies, Jitterbit, Talend, IBM, Adeptia, Pantheon, and Axway are Strong Performers; Red Hat is a Contender; and Microsoft is a Challenger. "The Forrester Wave™ Strategic iPaaS And Hybrid Integration Platforms, Q1 2019"