Advanced Techniques with Spark Declarative Pipelines

This course explores Databricks' Lakeflow Spark Declarative Pipelines (SDP) for building production-grade streaming pipelines. You will learn advanced design patterns, robust data quality enforcement, and cross-platform integration essential for real-world lakehouse engineering.

Throughout the course, you will dive into modern data ingestion and processing techniques, mastering tools like Liquid Clustering for layout optimization and the Multiplex Streaming pattern for mixed-schema events. By the end of the modules, you will know how to confidently handle schema evolution, automate Change Data Capture (CDC), and ensure data integrity.

Through lectures and hands-on demos, you will:

• Build multi-flow pipelines to ingest multi-source data into a unified Bronze table.

• Apply Liquid Clustering and Data Quality Expectations across Silver and Gold layers.

• Implement the Multiplex pattern with Iceberg UniForm for cross-platform data access.

• Automate SCD Type 2 history tracking using AUTO CDC INTO.

• Design zero-data-loss quarantine pipelines to audit and manage invalid records.

Note:

1. This course is part of the 'Advanced Data Engineering with Databricks' course series.

2. Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

Languages Available: English | 日本語 | Português BR | 한국어

Skill Level

Professional

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

• Spark Declarative Pipelines — Completion of the "Build Data Pipelines with Lakeflow Spark Declarative Pipelines" course, or familiarity with CREATE OR REFRESH STREAMING TABLE, CONSTRAINTS, and the Pipelines UI

• Delta Lake Fundamentals — Understanding of Delta tables and how Delta manages data files and transaction logs

• Streaming Concepts — Knowledge of micro-batch streaming, checkpointing, and event-time processing in SDP

• SQL Proficiency — Ability to read and write SQL, including SELECT, JOIN, MERGE, CASE WHEN, and common aggregate functions

• Python in Databricks Notebooks — Comfort with reading and running Python code in Databricks notebooks

• Unity Catalog Basics — Understanding of catalogs, schemas, tables, and volumes in Unity Catalog

Outline

• Introduction to Multi Flows, Expectation and Liquid Clustering in SDP

• Demo: Multi Flow SDP with Liquid Clustering and Data Quality

• Introduction to Multiplex Streaming, Delta Sinks and Iceberg Reads

• Demo: Multiplex Streaming SDP with Delta Sinks and Iceberg Reads

• Change Data Capture (CDC) Review

• Demo: Automating SCD Type 2 with AUTO CDC in Lakeflow Spark Declarative Pipelines

• Advanced Data Quality Checks and Expectations in SDP

• Demo: Advanced Data Quality Checks and Expectation in SDP

• Lab - Building Multi-Source Ecommerce Pipeline with SDP

Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	Jun 09	01 PM - 05 PM (Europe/London)	-	English	$750.00
Jun 11	08 AM - 12 PM (Asia/Kolkata)	-	English	$750.00
Jul 15	01 PM - 05 PM (Australia/Sydney)	-	English	$750.00
Jul 15	09 AM - 01 PM (America/New_York)	-	English	$750.00

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Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	Jun 09	01 PM - 05 PM (Europe/London)	-	English	$750.00
Jun 11	08 AM - 12 PM (Asia/Kolkata)	-	English	$750.00
Jul 15	01 PM - 05 PM (Australia/Sydney)	-	English	$750.00
Jul 15	09 AM - 01 PM (America/New_York)	-	English	$750.00

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