Modern Data Warehousing and the Lakehouse
Learn how cloud warehouses and Delta Lake power the modern stack: separate compute, time travel, ACID tables, MERGE, and the Medallion layers.
What You'll Learn
Understanding Why Your Data Platform Bill Can Suddenly Change
You have built acme-shop's batch pipelines and its S3 data lake.
Understanding Cloud Warehouse Architecture
The Data Warehouse Design and Query Performance module covered storage and compute separation as a general idea.
Recognising Warehouse Features Worth Knowing (Good to Know)
You do not need hands-on mastery of these. Recognise them and know the problem each one solves.
Understanding Why Plain Parquet Files Are Not Enough
A plain data lake stores files, often Parquet, directly in cloud storage.
Applying the Medallion Architecture
The Medallion Architecture organises a lakehouse into three progressively cleaner layers.
Recognising Iceberg, Compaction, and Z-Ordering (Good to Know / Optional)
These are performance and ecosystem topics that you should recognise but need not master.
Skills You'll Master
Curriculum Index9 topics
Understanding Why Your Data Platform Bill Can Suddenly Change
You have built acme-shop's batch pipelines and its S3 data lake.
Understanding Cloud Warehouse Architecture
The Data Warehouse Design and Query Performance module covered storage and compute separation as a general idea.
Recognising Warehouse Features Worth Knowing (Good to Know)
You do not need hands-on mastery of these. Recognise them and know the problem each one solves.
Understanding Why Plain Parquet Files Are Not Enough
A plain data lake stores files, often Parquet, directly in cloud storage.
Applying the Medallion Architecture
The Medallion Architecture organises a lakehouse into three progressively cleaner layers.
Recognising Iceberg, Compaction, and Z-Ordering (Good to Know / Optional)
These are performance and ecosystem topics that you should recognise but need not master.
Hands-On Lab: Build a Medallion Pipeline and Reproduce a Cost Incident
📌 Remember: This lab is free and runs locally with Spark and Delta Lake.
Quick Reference
Concepts and Tiers Snowflake Syntax Seen in This Module
Common Mistakes
Mistakes to Avoid Treating Time Travel as a backup. It feels like one, because you can query an old version.
Career Impact
Roles that use the skills in this module.
Data Engineer
Platform Engineer
Next Modules
Practice on the Coding Sheet
Not a software engineer sheet. Every problem comes from real DevOps, SRE, Platform and Cloud interviews, from your first script to a system you build yourself.
Open the Coding SheetFrequently Asked Questions
A lakehouse keeps data in cheap files in cloud storage, as a lake does, but adds a table layer that gives warehouse-like guarantees such as transactions, schema enforcement, and time travel. Delta Lake and Apache Iceberg are two common table formats.
No. Time Travel keeps old versions for a limited retention window so you can investigate or undo a recent mistake. Anything that must survive longer needs a separate, tested backup.
They are three layers of a Medallion pipeline. Bronze holds raw data as it arrived, Silver holds cleaned and deduplicated data, and Gold holds business-ready tables for dashboards.
No. Snowflake is used as the named example for warehouse features, with its real syntax clearly labelled. The hands-on lab runs locally with Spark and Delta Lake, and a Snowflake trial exercise is optional.