SQL Programming and Procedural Logic
In this course, you will explore core SQL programming and procedural logic skills within Databricks, focusing on how to build modular, maintainable, and production-ready analytics workflows. You’ll start by learning about key SQL constructs—such as Common Table Expressions, temporary views, and User Defined Functions—that make your SQL development cleaner and more reusable. The course then guides you through advanced SQL scripting techniques using compound statements, variables, control flow, conditionals, loops, and robust error handling to create structured and flexible SQL processes. Finally, you’ll discover how to orchestrate and modernize complex workflows with Lakeflow Jobs and migration strategies, transforming legacy tasks into modular, automated pipelines that leverage the full capabilities of the Databricks platform.
The content was developed for participants with these skills/knowledge/abilities:
⇾ A fundamental understanding of SQL workspaces, data warehouses, and Databricks notebooks (SQL, Python, and markdown)
⇾ Experience working with the Databricks Lakehouse architecture, including Delta Lake and Unity Catalog for data management and governance
⇾ Familiarity with creating and managing workflows for data pipelines and orchestration
⇾ Prior experience querying and analyzing data with SQL in relational databases, including use of stored procedures and dynamic or parameterized queries
⇾ A working knowledge of data migration or modernization projects, covering core data warehousing concepts such as ETL, schema design, data modeling, and BI Reporting
⇾ Awareness of data pipeline orchestration and compliance best practices, and understanding of ANSI SQL standards
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Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
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