Up to this point, most of the examples we looked at in this book assume that data is structured well and is fairly clean. Data in the real world isn't so pretty at times. Maybe it's messy or it doesn't have a good structure. Maybe it has missing values or duplicate values. Or maybe it is at the wrong level of detail.

How can you deal with this messy data? Tableau offers quite a bit of flexibility to address data issues within the tool. We'll take a look at some of the features and techniques that will enable you to overcome data structure obstacles. Having a good understanding of what data structures work well with Tableau is a key factor to understand how you will be able to resolve certain issues.

In this chapter, we'll focus on some principles that structure data to work well with Tableau as well as some specific examples of how to address common data issues. This chapter will cover the following topics: