This course comprises instructor-led discussions, demonstrations, and hands-on exercises designed to build a working knowledge of the Starburst query engine. Participants will gain a more thorough awareness of Starburst architecture, focusing on best practices for data lake based schemas, including table formats and partitioning, file formats and sizes, and other optimization techniques.

Upon completion of this course, you will be able to:
● Use Starburst as a single point of access for multiple data sources and federate queries across them
● Evaluate and describe how queries are executed within a Starburst cluster
● Use Hive and Iceberg table formats; construct, populate, query, and modify partitioned tables
● Employ file size/format/hierarchy strategies to improve query performance
● Understand the role of the Cost-based optimizer and read query plans to ensure optimizations are occurring as expected and to identify possible issues
● Create role-based access control policies for table operations
● Build a data engineering pipeline with Starburst Galaxy