Incremental Load in ETL | CDC, Checksum & Timestamps | SSIS | ADF | Data Engineering

Welcome to Cloud BI Academy! 🎯 In this video, we will learn one of the MOST important concepts in Data Engineering & ETL projects — Incremental Load. Whether you are working in SQL Server, SSIS, Azure Data Factory, Databricks, or any ETL tool, understanding incremental data loading is essential for performance, cost optimization, and real-time business reporting. 🚀 What You Will Learn: ✔ Why Full Load is not efficient ✔ What is Incremental Load? ✔ Real-time Incremental Load strategies:  ◾ CDC – Change Data Capture  ◾ Checksum / Hash Based Load  ◾ Timestamp / Watermark Based Load ✔ Pros & Cons of each approach ✔ Which approach to choose in Interviews & Projects ✔ Practical Data Engineering Best Practices 🧠 Interview Highlights: 🔹 Which incremental method captures deletes? 🔹 CDC vs Change Tracking — Key differences 🔹 Why timestamps may fail in projects 🔹 Real-time use cases & performance tips 🧩 Chapters: 00:00 – Intro 00:40 – Why Incremental Load? 02:20 – CDC Method 06:15 – Checksum Method 10:20 – Timestamp Method 14:30 – Comparison & Best Practice 17:00 – Interview Questions 19:30 – Summary 📥 Download Resources 📌 PPT, SQL Scripts & Diagrams: (Ask in comments — we will share!) 🔔 Connect & Learn More 📌 Subscribe for more practical ETL & Data Engineering tutorials! 💬 Comment your topic requests below 👇 👍 Like & Share this video with your team! Incremental Load SQL Server, ETL Incremental Load, CDC SSIS, Azure Data Factory Incremental Load, Change Data Capture Tutorial, Checksum Incremental Load, Watermark ETL, Data Warehouse Loading, SQL Interview Questions, SSIS Tutorial, ADF Tutorial, SQL BI Training, Data Engineering Basics