The difference between ETL and ELT pipelines, why ELT took off with cloud warehouses, and when transforming data before loading it is still the better choice.
What batch processing is, how batch jobs run under the hood, the tools that build and schedule them, their limits, and where batch still beats streaming.
What streaming data is, how producers, message brokers, and stream processors work together, real-time use cases, and the challenges of streaming pipelines.
Data modeling basics: OLTP versus OLAP systems, normalization and denormalization, star and snowflake schemas, and how to design models that can grow.
