Databricks Performance Optimization

In this hands-on course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, Photon, and more. 

Note: Hands-on training courses will be updated to reflect the newest product and feature announcements from Data + AI Summit in June 2026. 

Prerequisites

• Basic Databricks development skills, including creating clusters, running notebooks, and importing repos from Git
• Intermediate PySpark experience, including data extraction, transformations, and use of advanced built-in functions
• Intermediate Delta Lake experience, including creating tables, incremental updates, file compaction, and version restoration