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..