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

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.

Prior to Viking, Ben worked as Director of Data Science & Analytics at JetBlue where he led the Data Engineering, Business Intelligence, and Data Science teams. He also used to be the Director of Analytics at the New York Police Department, where he focused on building data platform capabilities and data products to support operational and strategic needs. He holds a B.A. from Yale University and an M.A. from John Jay College of Criminal Justice.

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

Ryan is an IT professional with 20 years experience delivering enterprise data solutions. He 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.

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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Last modified on: Dec 6, 2023