Databricks Academy offers Build Data Pipelines with Lakeflow Spark Declarative Pipelines, a course on the core concepts of Lakeflow Spark Declarative Pipelines on the Databricks Data Intelligence Platform, taught with a simple, SQL-based approach (with Python code examples provided).

You’ll learn to:

• Build incremental batch and streaming pipelines with Lakeflow Spark Declarative Pipelines
• Combine streaming tables, materialized views, and temporary views to power end-to-end pipelines
• Configure compute, data assets, trigger modes, and data quality expectations
• Use event logs, metrics, and AUTO CDC INTO to monitor pipelines and handle slowly changing dimensions

Designed for:

• Data engineers building or maintaining data pipelines on Databricks
• Learners with Databricks basics (workspaces, Delta Lake, Medallion Architecture, Unity Catalog)
• SQL users with experience in ingesting data into Delta tables

Course format & details:

• Syllabus: 3 Sections | 22 Lessons
• Duration: 2 hours 00 minutes
• Skill Level: Associate
• Cost: Free

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