What Is Change Data Capture - Understanding Data Engineering 101

Companies continue to look for methods to gain near-real-time access to their data for analytics. Honestly, this has been ongoing since I got into the data industry a decade ago…and well before that.

One possible choice is a method called change data capture, also known as CDC. I have seen companies employ multiple ways to use CDC or CDC-like approaches to pull data from databases like Postgres or MongoDB.

This can range from using triggers to reading logs.

Of course, this focuses on the analytical component as many companies use CDC to replace or supplement traditional ETL/ELT.

But CDC can also be a great way to understand your database and its structure. Databases abstract much of what they do to manage and process large volumes of data quickly.

Here are a a few articles on CDC if you need to learn more

How To Implement CDC With Kafka
https://bit.ly/3LII6z4

Simple CDC with Debezium + Kafka
  / simple-cdc-with-debezium-kafka  

0:00 - Intro
1:12 - Write Ahead Logs (WAL)
2:30 - Trigger Based CDC
4:30 - Examples Of Where I Have Used Change Data Capture

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About me:
I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.

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