We started this chapter comparing the term mise en place used by professional chefs to the task of loading and preparing the data before we start creating predictive models.

During this chapter, we introduced the basic vocabulary to describe datasets, observations, and variables. We also saw how to load a CVS file into Rattle and described the most usual data transformations.

This chapter, as well as Chapter 3, Exploring and Understanding Your Data, covered the mise en place for our data. After going through these chapters, we'll be able to prepare our data to analyze it and discover hidden insights.

In the next chapter, we'll explore the dataset to have a better understanding and to find data quality problems. The next two chapters are tied because exploring the dataset and transforming it are complementary tasks.

When you are cooking, the quality of the ingredients has a great influence on the quality of your dish. Working with data is very similar; it's very hard to achieve good results if you use low quality data. For this reason, these two chapters are really important.