Welcome to the next installment of our Analytics Journey, which explores how we at Ruths.ai apply the CRISP-DM method to our Data Science process. Previously, we looked at an overview of the methodology as a whole as well as the Business Understanding, Data Understanding, and Data Preparation stages. Next, we examine the Modeling stage.
We have finally reached the fun part! We have reached the step where we can move from a descriptive look back to a predictive look forward. In the Data Understanding phase, we discussed the 80-20 rule, which states that data professionals spend 80% of their time cleaning data, akin to the tedious hours of practice preparing for the big game. Hopefully, we have shown through phenomena like Simpson’s Paradox that even the Data Understanding/Preparation stages can bring intriguing insight; however, the Modeling stage represents the true opportunity and most intellectually stimulating phase.