Summary
We began this chapter with a discussion on complex joins and discovered that when possible, Tableau uses join culling to generate efficient queries of the data source. A secondary join, however, limits Tableau's ability to employ join culling. An extract results in a materialized, flattened view, which eliminates the need for joins to be included in any queries.
Next we reviewed data blending to clearly understand how data blending differs from joining. We discovered that the primary limitation in data blending is that no dimensions are allowed from a secondary source; however, we also discovered that there are exceptions to this rule. We also discussed scaffolding, which can make data blending surprisingly fruitful.
Finally, we discussed data structures and learned how pivoting can make difficult or seemingly impossible visualizations easy.
Having completed our second data-centric discussion, we will continue with another chapter that also includes All about Data in the title. Specifically...
