Deploying your data science models into production often requires complex processes and resources that can lead to the failure of your data project. How do companies handle this process?
We decided to ask thousands of companies how they handled the production phase of their data projects and launched a global survey a few months back.
We've now analyzed the results intensely and packaged them in a report full of actionable insights to help build or review the design-to-production pipeline. We've identified four profiles corresponding to four ways that companies today have set up their data science production processes. Check them out below- click on the infographic to make it bigger.
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