Sometimes, the dataset we have is not always in the right shape for it to be consumed by machine learning algorithms. In such conditions, data preparation is one of the most essential things we can do. We need to integrate data from several sources, perform slicing and grouping, and aggregate them into the correct format and structure. This step is referred to as data preparation. 

We discussed this process in detail in Chapter 6, Grouping Datasets. It is essential to note that some books consider data preprocessing and data preparation as the same step as there are several overlapping operations.