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Structuring Messy Data to Work Well in Tableau
So far, most of the examples we've looked at in this book assume that data is structured well and is fairly clean. Data in the real world isn't always so pretty. Maybe it's messy or it doesn't have a good structure. It may be missing values or have duplicate values, or it might have the wrong level of detail.
How can you deal with this type of messy data? In the previous chapter, we considered how Tableau's data model can be used to relate data in different tables. We will consider Tableau Prep Builder as a robust way to clean and structure data in the next chapter. Much of the information in this chapter will be an essential foundation for working with Tableau Prep.
For now, let's focus on some ...
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