Post by Prateek Jalgaonkar

🔍 CDC vs SCD — Why We Get Confused (A Simple Explanation) If you're on your Data Engineering journey, you’ve probably heard the terms CDC (Change Data Capture) and SCD (Slowly Changing Dimensions). They sound similar… but they do very different things. Let me explain with a simple example 👇 🟦 CDC → Detecting the Change CDC is all about capturing what changed in the source system. Example: If a customer record gets deleted in the source database, CDC will generate an event like: Operation: DELETE Customer_ID: 101 Timestamp: 2025-03-11 CDC does NOT store history. Its only job is to inform you that a change occurred (INSERT/UPDATE/DELETE). 🟩 SCD → Storing the Change Historically Once CDC tells us that Customer 101 was deleted… Inside the Data Warehouse, we update our dimension table to maintain history. For example, we might: Mark is_deleted = true Or close the record using valid_to = delete_timestamp Or create a new version (SCD Type 2) This part — preserving history — is what SCD is all about. 🎯 Quick Summary ✔️ CDC = “Hey! Something changed in the source!” ✔️ SCD = “Let me store this change historically in the warehouse.” Both work together, but their purposes are different. 📌 Why this matters Understanding this difference helps you design: Reliable ETL/ELT pipelines Historical reporting Slowly changing dimensions Audit-friendly data models And it prevents confusion when dealing with deletes, updates, and late-arriving data. #DataEngineering #BigData #DataScience #Cloud #ETL #DataArchitecture, #Analytics #AI #Innovation #Technology #Leadership #Career