Learning Series | Data Modeling Strategies

Tushar_Parekar — Thu, 18 Jun 2026 14:40:36 GMT

Databricks Academy offers the free Data Modeling Strategies course to help data practitioners understand and apply different modelling approaches on the Databricks Data Intelligence Platform. It covers a broad range of strategies, from traditional warehouse modelling methods like Inmon, Kimball, and Data Vault 2.0 to modern use cases such as Feature Store and Data Products on Unity Catalog.

You’ll learn to:

Compare core modelling approaches: Understand the differences between Inmon, Kimball, and Data Vault 2.0, and when each approach fits best.
Build modern Lakehouse data models: Learn how modelling fits into the Bronze, Silver, and Gold layers, including relational integrity, star schemas, and vault structures.
Support ML and data product use cases: Explore how Feature Store and Data Products on Unity Catalog extend modelling into machine learning and governed sharing.
Choose the right strategy for the job: See how warehouse, vault, feature, and product-based approaches can work together in a practical Lakehouse architecture.

Designed for:

Data architects and data practitioners working on Databricks
Users with working knowledge of SQL and relational database concepts
Learners familiar with Databricks fundamentals and medallion architecture

Course format & details:

Syllabus: 3 sections | 17 lessons
Duration: 2 hours
Skill level: Associate
Cost: Free
Includes labs: No
Languages: English, Japanese, Portuguese BR, Korean

Recent updates:

Framed Metric Views, Feature Store, and Delta Sharing as Gold-layer pillars for BI, ML, and collaboration
Updated the course to use Serverless compute

Important note:

For SCORM lecture files, close the SCORM window after completing the content. Do not click Next Lesson, as that may prevent the module from being marked complete.