Udemy - Databricks Data Engineering with DLT and Lakeflow Pipelines [TorrentX]

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.