Up to this point, most of the examples we've looked at in this book assume that data is well structured and 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. It may be missing values or have duplicate values. It might be at the wrong level of detail.
How can you deal with this messy data? Tableau offers quite a bit of flexibility for addressing 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 the key to understanding how you will be able to resolve certain issues.
In this chapter, we'll focus on some principles for structuring 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:
- Structuring data for Tableau
- Techniques for dealing...