You’ve got your pipelines flowing … how much do you know about the data inside?

Most teams have some coverage with unit/contract/expectations tests, and you might have other quality checks. But it can be very ad-hoc and disorganized. You want to do more to beef up data quality and observability … does that mean you just need to write more tests and assertions?

Come learn about the best way to see your data’s quality alongside DAGs in a familiar context. We’ll review 3 common tools to get a handle on quality in a cohesive way across all your DAGs:

  • Great Expectations
  • Monte Carlo Data
  • Databand