Level 11: The Data Pipeline
Processing data at scale: batch, stream, event sourcing, and modern data architectures.
Welcome to Level 11
When data grows beyond what a single database can handle, you need pipelines. This level covers batch processing, stream processing, event sourcing, change data capture, and modern data architectures.
| Module | Topic |
|---|---|
| 11.1 | Batch Processing (MapReduce, Spark) |
| 11.2 | Stream Processing (Kafka Streams, Flink) |
| 11.3 | Event Sourcing and CQRS |
| 11.4 | Change Data Capture |
| 11.5 | Data Architectures (Lambda, Kappa, Data Mesh) |
| 11.6 | Checkpoint |
Key Takeaway
Data pipelines move, transform, and analyze data at scale. Understanding the spectrum from batch to real-time and choosing the right architecture is essential for data-intensive systems.
Connect
Start with Module 11.1: Batch Processing — the original big data paradigm.