Summary
In this chapter, you learned about common usages of the ETL pattern, including integration, aggregation, modularization, and performance. The integration patterns offer a lowest-common-denominator approach to connecting disparate systems, even if they have no native support for integrating with each other. ETL for aggregations helps produce a single source of truth (SSOT) for getting a view of data across your estate. This is a common pattern for creating data lakes that work with services such as Athena. Modularization is an approach for using ETL to break up monolithic processes that are difficult to maintain or operationally prone to failure. Lastly, ETL for performance is a technique that moves expensive or time-consuming processing out of the live query path by either creating materialized views or running other pre-computations of anticipated workloads.
Armed with this knowledge of ETL design patterns, you reviewed key criteria for designing ETL queries for use with...
