Table of Contents

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

Leveraging dbt metadata in data management

Sam entered the data management industry in 2018 as graduate. Since then he has been involved in a wide range of disciplines, including standing up data quality programmes, implementing data governance tools and developing best-practice processes encompassing data through its lifespan. Outside of work, Sam enjoys working on personal software development projects and making music.

Originally presented on 2020-12-13

Effective data governance, lineage and discoverability are key to fully leveraging data within an organization. In this talk, we'll discuss why these processes are so important to a high-functioning data organization. We'll also share how we are using the metadata artifacts from dbt runs to provide additional insight to inform data governance and discoverability through a dbt integration we've built for Collibra, a metadata management tool.

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