Udemy - Databricks Data Engineering with DLT and Lakeflow Pipelin...

Databricks Data Engineering with DLT & Lakeflow Pipelines

https://WebToolTip.com

Published 8/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 4h 20m | Size: 3.1 GB

Databricks | Master streaming pipelines, Auto Loader, CDC, SCD Type 1/2 & data quality governance with Delta Live Tables

What you'll learn
Build and manage production-ready Delta Live Tables (DLT) and Lakeflow Declarative Pipelines from scratch
Ingest file-based live streaming data using Auto Loader
Handle schema inference and schema evolution in production environments
Merge multi-source data streams into unified tables using Append Flows architecture
Capture real-time source changes with Change Data Capture (CDC) and Auto CDC Flow
Implement enterprise SCD Type 1 and SCD Type 2 architectures on DLT
Set up automated data quality rules and isolate bad data using DLT Expectations
Build dynamic, parameter-driven pipelines that adapt at runtime
Optimize pipeline performance and manage workspace costs
Monitor pipeline health, lineage, and handle production errors

Requirements
A basic understanding of SQL or Python is enough for you to grasp data querying logic easily.
A general familiarity with foundational data engineering concepts, such as ETL, databases, and table structures, is required.
Prior familiarity with the Databricks interface is an advantage; however, it is not mandatory thanks to the orientation lessons included in the course.
A computer with an internet connection is all you need to follow the hands-on applications; no local software installation is required.