1.3 THE DATA SCIENCE METHODOLOGY
We follow the Data Science Methodology (DSM),4 which helps the analyst keep track of which phase of the analysis he or she is performing. Figure 1.1 illustrates the adaptive and iterative nature of the DSM, using the following phases:
- Problem Understanding Phase. How often have teams worked hard to solve a problem, only to find out later that they solved the wrong problem? Further, how often have the marketing team and the analytics team not been on the same page? This phase attempts to avoid these pitfalls.
- First, clearly enunciate the project objectives,
- Then, translate these objectives into the formulation of a problem that can be solved using data science.
- Data Preparation Phase. Raw data from data repositories is seldom ready for the algorithms straight out of the box. Instead, it needs to be cleaned or “prepared for analysis.” When analysts first examine the data, they uncover the inevitable problems with data quality that always...