Data scientists have come up with a strategy to build the right model that captures data science. As a first step one needs to think big, yet start with small steps. The KISS principle or Keep It Short and Simple, needs to be followed. The 80- 20 Pareto Principle would also apply here. Another tip is to focus on finding the model, instead of building it. Of course, any such model, would require a through data warehousing operation, before anything could be concretely firmed up. Organizations need not lose sleep over failures. Instead, they must learn quick. The error rate needs to be checked for.

Source:https://www.boozallen.com/s/insight/blog/kirk-borne-on-building-data-science-models.html

Uploaded Date:21 December 2019