In this chapter, we explored Google Cloud Dataprep, a service useful to preprocess the data, extract features, and clean up records. We got into practical details with real-life examples. We started by taking a look at the Cloud application interface to discover some preliminary information needed to access the platform. We then analyzed the techniques available for the preparation of the most suitable data for analysis and modeling, which includes the imputation of missing data, detecting and eliminating outliers, and mismatched values treatment. We discovered different ways to transform data and the degree of cleaning data. Then we learned how to normalize our data, in which data units are eliminated, allowing us to easily compare data from different locations.