Table of Contents

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

Implementing dbt at large enterprises

With more than 25 years of application and analytics development and management, Chris leads the consulting services division of Visual BI Solutions. Visual BI is an end-to-end modern analytics solutions company delivering consulting services and application development to medium to large enterprises.

Amy hails from the land of chemical manufacturing as a former chemist. She is excited to start on this new adventure of data consulting. When not exploring the wonders of SQL and dbt, she’s up in the air doing aerials or rock climbing.

Ryan is an IT professional with 20 years experience delivering enterprise data solutions. Ryan is an experienced leader, who has worked with teams to adopt new technologies through the practical application of architecture models, processes, best practices, roadmaps, operational improvement, and governance models.

Ben is the Director of Data Science & Analytics at JetBlue where he leads the Data Engineering, Business Intelligence, and Data Science teams. The JetBlue Data Team recently implemented a modern data stack featuring Snowflake and dbt. Prior to JetBlue, Ben was the Director of Analytics at the New York Police Department he focused on building data platform capabilities and data products to support operational and strategic needs. Before that, Ben worked at Sidewalk Labs (an Alphabet company) and the Manhattan DA's Office. He holds a B.A. from Yale University and a M.A. from John Jay College of Criminal Justice.

Originally presented on 2020-12-13

What does it look like to implement dbt at an organization where the number of employees is in the thousands? In this session we'll learn from the people who have answered exactly this question at organizations like JetBlue and Chesapeake Energy.

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