Introduction to Databricks Lakehouse

Data lakes offer flexibility but lack reliability. Data warehouses deliver performance but can't handle unstructured data. The lakehouse combines both — and Databricks is where it all comes together. In this course, you'll explore the Databricks Lakehouse from the ground up, gaining hands-on experience with the platform's core components.

Understand the Lakehouse Architecture

Start by discovering what sets the lakehouse apart from traditional approaches. You'll explore the medallion architecture — bronze, silver, and gold layers — that transforms raw, messy data into clean, business-ready insights. Then get oriented inside the Databricks workspace to understand how catalogs, schemas, and volumes organize everything.

Master Compute and Notebooks

Learn to choose the right cluster for the job, configure autoscaling and auto-termination to control costs, and build notebooks that mix Python, SQL, and Markdown. You'll also connect your work to Git through Databricks Repos for version control and team collaboration.

Govern and Share Data Securely

Explore Unity Catalog to manage access controls and track data lineage across your organization. Then use Delta Sharing to distribute data to partners — on Databricks or any other platform — and query external sources with Lakehouse Federation, all without copying a single byte.

Deploy to Production with Asset Bundles

Wrap up by packaging your notebooks, pipelines, and jobs into Databricks Asset Bundles for repeatable, automated deployments. A capstone scenario brings everything together so you leave ready to apply these skills on the job.