Build Data Pipelines with Lakeflow Declarative Pipelines

This course introduces users to the essential concepts and skills needed to build data pipelines using Lakeflow Declarative Pipelines in Databricks for incremental batch or streaming ingestion and processing through multiple streaming tables and materialized views. Designed for data engineers new to Lakeflow Declarative Pipelines, the course provides a comprehensive overview of core components such as incremental data processing, streaming tables, materialized views, and temporary views, highlighting their specific purposes and differences.

Topics covered include:

- Developing and debugging ETL pipelines with the multi-file editor in Lakeflow using SQL (with Python code examples provided)

- How Lakeflow Declarative Pipelines track data dependencies in a pipeline through the pipeline graph

- Configuring pipeline compute resources, data assets, trigger modes, and other advanced options

Next, the course introduces data quality expectations in Lakeflow, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, production mode, and enabling pipeline event logging to monitor pipeline performance and health.

Finally, the course covers how to implement Change Data Capture (CDC) using the APPLY CHANGES INTO syntax within Lakeflow Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.

Skill Level

Associate

Duration

Prerequisites

⇾ Basic understanding of the Databricks Data Intelligence platform, including Databricks Workspaces, Apache Spark, Delta Lake, the Medallion Architecture and Unity Catalog.

⇾ Experience ingesting raw data into Delta tables, including using the read_files SQL function to load formats like CSV, JSON, TXT, and Parquet.

⇾ Proficiency in transforming data using SQL, including writing intermediate-level queries and a basic understanding of SQL joins.

Outline

Introduction to Data Engineering in Databricks

⇾ Data Engineering in Databricks

⇾ What are Lakeflow Declarative Pipelines?

⇾ Course Setup and Creating a Pipeline

⇾ Course Project Overview

Lakeflow Declarative Pipeline Fundamentals

⇾ Dataset Types Overview

⇾ Simplified Pipeline Development

⇾ Common Pipeline Settings

⇾ Developing a Simple Pipeline

⇾ Ensure Data Quality with Expectations

Building Lakeflow Declarative Pipelines

⇾ Streaming Joins Overview

⇾ Deploying a Pipeline to Production

⇾ Change Data Capture (CDC) Overview

⇾ Change Data Capture with Apply CHANGE INTO

⇾ Additional Features Overview

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