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 and her team have been working with dbt for the past several months, and have used it to give their enterprise data warehouse a complete makeover. She loves working with dbt and believes it is an essential ingredient for building a modern data warehouse.

You probably have customer data in your [data warehouse](https://docs.getdbt.com/terms/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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