Get Started with Databricks for Data Warehousing

This course provides a comprehensive, hands-on overview of Databricks' modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. Working end-to-end with a fictional retailer (Vintage Audio Co.), you will explore the workspace, query governed Unity Catalog tables, keep Unity Catalog managed tables fast for analytical reads, load data incrementally with Auto Loader, model a star schema, and deliver consistent insights through Unity Catalog metric views — all from a single, governed environment, with AI-driven features (Predictive Optimization, Genie Code) built in throughout.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Skill Level

Onboarding

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

• Basic familiarity with the data warehousing domain (what a data warehouse, a table, and BI tools are).

• Working knowledge of SQL (SELECT with WHERE, GROUP BY, aggregate functions, and JOIN).

• No prior Databricks knowledge is assumed; Databricks-specific concepts (Unity Catalog, Delta Lake, SQL Warehouses, metric views) are introduced as they come up.

Outline

• Databricks Data Intelligence Platform

• Demo: Databricks Workspace Walkthrough

• Demo: Querying the Vintage Audio Warehouse

• Lab: Explore the Vintage Audio Tables

• Demo: Tuning Unity Catalog managed Tables for Analytical Queries

• Lab: Optimize the Products Table

• Demo: Loading Data into the Warehouse

• Lab: Incrementally Load New Orders

• Demo: Building a Star Schema

• Lab: Build a Store Dimension

• Demo: Deliver Insights with Metric Views

• Lab: Create a Metric View for Store Performance

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Proof of completion

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