We began this chapter with a discussion of the Tableau data handling engine. This illustrated the flexibility Tableau provides in working with data. The data handling engine is important to understand in order to ensure that data mining efforts are intelligently focused. Otherwise, effort may be wasted on activities not relevant to Tableau.
Next, we discussed data mining and knowledge discovery process models, with an emphasis on CRISP-DM. The purpose of this discussion was to get an appropriate bird's-eye view of the scope of the entire data mining effort. Tableau authors (and certainly end users) can become so focused on the reporting produced in deployment so as to forget or short-change the other phases, particularly data preparation.
Our last focus in this chapter was on that phase that can be the most time-consuming and labor-intensive, namely data preparation...