Data Engineering With AWS Chapter 7 Part 2: Transforming Data - Optimization and Business Logic
This is post 12 in my Data Engineering with AWS retelling series.
In Part 1, we covered the generic data preparation transforms: converting to Parquet, partitioning, PII protection, and data cleansing. Those transforms work on individual datasets and do not need much business context. Now we get to the transforms that actually create business value. The ones that combine multiple datasets, add context, flatten structures, and produce the tables that analysts and dashboards consume.