Table of Contents

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

Perfect complements: Using dbt with Looker for effective data governance

Johnathan is a solutions architect who is excited about helping data folks unleash the power and flexibility of the modern data stack and analytics engineering principles. He works at 4 Mile Analytics - a full-stack data consultancy - designing and developing analytics solutions built around Looker and dbt to elevate data teams to the next level of analytics maturity. Johnathan has worked as a senior data engineer, product manager, and a data analyst in the past. In his spare time, he enjoys playing 'name that tune', a game of Super Smash Bros, and dancing (even though he doesn’t know how).

Originally presented on 2020-12-14

Learn how a rapidly growing software development firm transformed their legacy data analytics approach by embracing analytics engineering with dbt and Looker. We’ll outline the complementary benefits of these tools and discuss design patterns and analytics engineering principles that enable strong data governance, increased agility and scalability, while decreasing maintenance overhead.

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