How to implement a Data Vault 2.0 architecture within a modern cloud data warehouse?

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Data Vault 2.0 is excellent for auditability and agility. Since cloud warehouses use columnar storage and massive parallel processing (MPP), the "join penalty" that used to kill Data Vault on old row-based databases is much less of an issue now. The key is to keep your Vault as the "Source of Truth" and then build "Information Marts" (which can be Star Schemas) on top of it using views. This gives you the resilience of the Vault for storage and the performance of the Star Schema for the end-users. It also makes "reloading" history much easier when business rules change.

   Answered 2025-02-08 by Melissa Wagner

Are you planning to use an automation tool like dbt or Coalesce to manage the boilerplate code, or are you going to write the DDL for every Hub and Link manually?

   Answered 2025-02-11 by Kevin Harrison

• Kevin, we are definitely looking at dbt. I've seen some packages like dbtvault that seem to automate the creation of the hashing and metadata columns. Trying to do Data Vault manually seems like a recipe for disaster given the number of tables involved. My main goal is to ensure that if our ERP system adds three new columns next month, our core warehouse ingest doesn't fail, but instead just creates a new Satellite to capture that data without impacting our existing reports.

     Commented 2025-02-13 by Thomas Anderson

Data Vault is a lifesaver for GDPR compliance. Having separate Satellites for PII data makes it much easier to "forget" a user without destroying the integrity of your transaction Links.

   Answered 2025-02-15 by Barbara Miller

• I never thought about the GDPR angle, Barbara! That’s a huge selling point for our legal team and might be the "killer feature" that gets this project approved.

     Commented 2025-02-17 by Melissa Wagner