The Engineering Side of Data cover image

Data Pipeline Testing with Bartosz Mikulski

The Engineering Side of Data

00:00

How to Handle Bad Data in Production

When these tools see a range, a value of a column falls outside of a range, right? And you get an error. Is that, how do you recommend that typically handled in production? Are those errors logged? Are there notifications sent out? What have you seen as a good way to kind of mitigate that bad data once these tools find it in production? I'm not sure if that's good. But what makes sense for me is by separating the data into, like, maybe two buckets, like the data that is correct and data that is incorrect.

Transcript
Play full episode

The AI-powered Podcast Player

Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
App store bannerPlay store banner
Get the app