Table of Contents

  1. Data transformation
  2. Data testing
  3. Implementations + deployment
  4. Documentation + metadata
  5. The modern data stack
  6. Data dream teams

Building a robust data pipeline with dbt, Airflow, and Great Expectations

Sam is an all-round data person in New York City with a passion for turning high quality data into valuable insights. Sam holds a PhD in Computer Science and has been working for several data-focused startups in recent years.

Originally presented on 2020-12-12

How do dbt and Great Expectations complement each other? This talk will outline a convenient pattern for using these tools together and highlight where each one can play its strengths: Data pipelines are built and tested during development using dbt, while Great Expectations can handle data validation, pipeline control flow, and alerting in a production environment.

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