Resources about the purpose and the importance of a data science platform for businesses, including examples of various platforms like Continuum Analytics, Adatao and more.

Data Science Platforms

Learn More About Popular Data Science Platforms

Perspectives on Data Science Platforms

L;;Data Science Platform: What is it and Why is it Important?;;NA;NA;;;As more companies recognize the need for a data science platform, more vendors are claiming they have one. Increasingly, we see companies describing their product as a “data science platform” without describing the features that make platforms so valuable. This article describes the core capabilities a platform should have in order for it to be valuable to data science teams.
L;;Data Science & Machine Learning Platforms for the Enterprise;;;;;
L;;The Move Towards Data Science Platforms;;;;;
L;;The Purpose of Platforms in Data Science;;NA;;;
L;;Data Science Platforms Seen as Difference-Makers;;NA;;;
L;;Why Businesses Use Data Science Platforms;;NA;;;
L;;What Is a Data Science Platform and Why Does Your Business Need One?;;NA;;;

Specific Environments

L;;Seven Python Tools All Data Scientists Should Know How to Use;;NA;;;


L;;Cooladata: Join Data Across All Your Customer Touchpoints;;NA;NA;;;Integrate your data from any source or database to one single data point – managed and built to scale. Connect the data points across customer touchpoints to understand the steps in each customer's journey.
L;;19 Data Science Tools for people who aren't so good at Programming;;NA;;;
L;;The Data Science Toolkit: 24 Free Data Science Tools;;NA;;;

Further Reading