Summary

In this chapter, you learned about two prominent methodologies of data processing known as ETL and ELT and saw the advantages of using ETL to unlock more analytics use cases than what's possible with ETL. By doing this, you understood the scalable storage and compute requirements of ETL and how modern cloud technologies help enable the ELT way of data processing. Then, you learned about the shortcomings of using cloud-based data lakes as analytics data stores, such as having a lack of atomic transactional and durability guarantees. After, you were introduced to Delta Lake as a modern data storage layer designed to overcome the shortcomings of cloud-based data lakes. You learned about the data integration and data cleansing techniques, which help consolidate raw transactional data from disparate sources to produce clean, pristine data that is ready to be presented to end users to generate meaningful insights. You also learned how to implement each of the techniques used...