Summary
This chapter covered data warehouses and data lakes, essential tools for data engineers. We studied these systems’ architecture, operation, and best practices. We started with data warehouses and how they use data marts and schemas to analyze structured transactional data. We examined their layered architecture and the ETL process, which underpins data warehouse operations.
Data lake architecture—from data ingestion and storage to data processing and cataloging—was our next topic. We explained data lake zones and their importance to organization and functionality. The difference between a well-managed data lake and a data swamp and the importance of data governance and security was stressed.
The next chapter will explore data engineering’s exciting CI/CD world. Prepare to learn about data engineering software development principles and practices that ensure efficiency and reliability. Let’s keep learning data engineering skills.
