Summary

This chapter detailed how data profiling is crucial for ensuring the quality, integrity, and reliability of datasets. The process involves in-depth analysis to understand the structure, patterns, and potential issues within the data. For effective profiling, tools such as pandas profiling and Great Expectations offer powerful solutions. Pandas profiling automates the generation of comprehensive reports, providing valuable insights into data characteristics. Great Expectations, on the other hand, facilitates the creation of data quality Expectations and allows for systematic validation. While these tools excel in smaller datasets, scaling profiling to big data requires specialized approaches. Learning the tips and tricks, such as data sampling and parallel processing, enables efficient and scalable profiling on large datasets.

In the next chapter, we will focus on how to clean and manipulate data to make sure it is in the right format to pass Expectations and be successfully...