How to structure business problems for data science solutions


Half the battle in a successful data science project can be expressing the problem in a way that ensures a optimal data-driven solution, with a clear set of realistic, achievable objectives. What exactly will be the commercial benefit of solving this problem? If you have properly addressed the first 3 points, this should be a yes, but it always worth this final check. It is at points 3 and 4 that seemingly well-structured data projects often become unstuck. A granular analysis at this stage can save much subsequent hair-tearing and disappointment.

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