Tableau can be a very effective tool for simply surveying data. Sometimes in the survey process you may discover ways to clean the data or populate incomplete data based on existing fields. Sometimes, regretfully, there are simply not enough pieces of the puzzle to put together an entire dataset. In such cases, Tableau can be useful to communicate exactly what the gaps are, and this, in turn, may incentivize the organization to more fully populate the underlying data.
In this exercise, we will explore how to use Tableau to quickly discover the percentage of null values for each field in a dataset. Next, we'll explore how data might be extrapolated from existing fields to fill in the gaps.
