Lab: Lakehouse Concepts

Explore the data lakehouse architecture hands-on: compare architectures, inspect platform components, and create your first Delta table.

Objectives

  • Identify key properties of a data lakehouse
  • Compare lakehouse vs data warehouse vs data lake
  • Create a Delta table and inspect the transaction log
  • Verify the Databricks environment

Lab Exercise

See labs/course1/week1/lab_lakehouse.py

Key Tasks

  1. Verify environment — Print Spark version and runtime info
  2. Architecture comparison — Build a DataFrame comparing warehouse/lake/lakehouse features
  3. Create Delta table — Write sample data as a Delta table
  4. Inspect history — Use DESCRIBE HISTORY to view the transaction log

Validation

The lab includes a validate_lab() function that checks:

  • Spark environment is running
  • Delta table was created with at least 5 rows
  • Architecture comparison DataFrame has all 3 architectures