Table of Contents

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

Securing data at scale with dbt & Snowflake

Ashley is the Manager of Data Engineering at JetBlue. She and her team have been working with dbt for the past 8 months, and have used it to give their enterprise data warehouse a complete makeover. Ashley loves working with dbt and believes it is an essential "ingredient" for building a modern data warehouse.

Originally presented on 2020-12-11

You probably have customer data in your data warehouse — it's a must-have for understanding a business. However, this data almost definitely includes personally identifiable information (PII), which shouldn't be shared with the entire organization. In this session, we'll learn how JetBlue approaches the problem of masking PII at scale by leveraging some Snowflake features straight from their dbt project.

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