Summary
In this chapter, we learned about a data lake and its various characteristics, such as multiple zones, the ability to deal with multiple formats, governance, and—most importantly—its ability to decouple storage and compute.
We also learned about four key data lake architectures: traditional, Lambda, Kappa, and Lakehouse. We analyzed each one from their applicability to certain case scenarios, costing, and overall management.
In the next chapter, I will highlight various tools and services available in Microsoft Azure required to build a data lake using the Lakehouse architecture.
