What’s a Data Science Platform?

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. So we wanted to share our vision for the core capabilities a platform should have in order for it to be valuable to data science teams. We see “the data science lifecycle” spanning three phases. Each phase has distinct demands that motivate capabilities for a data science platform: Ideation and exploration Experimentation & model development Operationalization / deployment To some degree, all data science projects go through these phases. Additionally, there is an underlying perspective that spans across this lifecycle: the need to manage, scale, and evolve your analyses and your…


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