There’s a part of data science that you never hear about: the production. Everybody talks about how to build models, but not many people worry
about how to actually use those models. Yet production issues are the reason many companies fail to see value come from their data science efforts.
Dataiku, company that develops a collaborative data science software platform aimed towards helping data teams deliver big data solutions and services efficiently, wondered how companies handled their production processes and environments to build production-ready data products, and they figured the easiest way to find out was to ask them. They conducted a worldwide survey and asked thousands of companies. And they got their answers.
After analyzing those answers, they isolated four different ways companies are dealing with production today, and they put together a series of
recommendations on how to build production-ready data science projects.
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