If you’ve ever worked with SQL Server and wondered how to keep track of every insert, update, and delete that happens inside your database, then you’re in the right place. In this video, I’m going to walk you through Change Data Capture (CDC) in SQL Server step by step. We’ll start from the very basics of what CDC is, why it matters, and why so many organizations rely on it. Then we’ll actually get our hands dirty — I’ll show you how to configure Change Data Capture inside SQL Server, how to enable it on a test database, create some test tables, insert test data, and then demonstrate how CDC automatically tracks the changes for us. By the end of this tutorial, you’ll not only understand what CDC does, but you’ll also be confident enough to implement it yourself in your own SQL Server environment. What is Change Data Capture (CDC)? At its core, Change Data Capture is a feature in SQL Server that helps you track data changes in your tables. Anytime a row is inserted, updated, or deleted, CDC records those changes in special system tables. Think of it like having a detailed log that captures the exact history of your data — without you having to manually write triggers or custom auditing code. This makes CDC one of the most powerful out-of-the-box features SQL Server provides for data tracking, auditing, and ETL processes. In simple terms, CDC allows you to answer questions like: Who changed what data? When was the change made? Was it an insert, an update, or a delete? What was the data before and after the change? Instead of having to guess or hunt through transaction logs manually, CDC makes all of this available in a structured way that’s easy to query with T-SQL. Why Would Organizations Use CDC? Organizations use Change Data Capture in SQL Server for several reasons. The most common one is auditing. In industries where compliance is critical — finance, healthcare, insurance, banking, government — it’s often a legal requirement to keep track of data modifications. For example, if a patient record is updated in a healthcare database, the organization needs a clear trail of that change. CDC provides this without the overhead of writing custom audit tables or triggers. Another major use case is for data warehousing and ETL pipelines. If you’ve ever worked on a data warehouse project, you know that capturing only the changes instead of copying the entire source table over and over again saves a massive amount of time and resources. With CDC, SQL Server tracks incremental changes, which makes ETL jobs in SSIS, Azure Data Factory, or other data integration tools much more efficient. CDC is also extremely useful for replication and synchronization scenarios. Imagine you have a reporting database that needs to stay up to date with changes happening in your OLTP (online transaction processing) database. Instead of moving entire tables, you can use CDC to pull only the delta changes and keep the systems synchronized in near real-time. Why is CDC Handy for DBAs? From a DBA perspective, Change Data Capture is a lifesaver. If you’re responsible for managing SQL Server environments, you already know how painful it can be when someone asks: “Who changed this record?” or “Why is this value different from last week?” Without CDC, you’d be forced to dig through SQL Server transaction logs, use third-party log readers, or rely on custom triggers — all of which are time-consuming and not always reliable. With CDC enabled, DBAs can quickly run a query against the CDC tables and provide an exact history of changes. This makes troubleshooting easier, helps with accountability, and improves transparency across the entire organization. For performance monitoring and compliance reporting, DBAs can rely on CDC instead of reinventing the wheel. Content of the Video 00:00 What is Change Data Capture (CDC) 00:26 Configuring CDC 02:12 SQL Agent Jobs 03:15 Test Data Changes 04:09 View CDC tables