Summary
In this chapter, we looked at Ask Data and Explain Data. These machine learning features put analysis in the hands of casual users if the data is modeled properly for each feature.
Ask Data requires us to first create a published data source. Next, we must create a lens on our published data source. A lens allows us to hide fields, rename fields, add synonyms, and create view recommendations. If we create a better lens, analysis by casual users through full-text search will provide much better answers.
By default, Explain Data runs statistical models that evaluate all the dimensions in our data model. We often know that some of these dimensions might appear in determining outliers but have no business value in the analysis. In these cases, we can remove dimensions from the analysis Tableau performs, increasing trust in the results of Explain Data.
In the next chapter, we will be looking at the role Tableau Prep Conductor plays in data modeling in the Tableau platform...
