Since Data Vault is pattern-based, the first layer of testing ensures the "plumbing" follows the methodology.

Intentionally feed "bad" data into the pipeline to ensure it is caught by error Satellites rather than crashing the load. Success Metrics (KPIs)

Verify that the hashing algorithm (MD5 or SHA-1) produces identical keys for the same business keys across different source systems. 4. Point-in-Time (PIT) & Bridge Table Validation

Data Vault should allow for high-concurrency loading.

Insert a record with a modified attribute. Verify that a new Satellite record is created with the updated data while the old record remains (historical tracking).

Test the performance of PIT tables; they should significantly speed up the joining of multiple Satellites.

The "Information Mart" layer is where users actually query the data.

Warehouse - Testing Data Vault-based Data

Since Data Vault is pattern-based, the first layer of testing ensures the "plumbing" follows the methodology.

Intentionally feed "bad" data into the pipeline to ensure it is caught by error Satellites rather than crashing the load. Success Metrics (KPIs) Testing Data Vault-Based Data Warehouse

Verify that the hashing algorithm (MD5 or SHA-1) produces identical keys for the same business keys across different source systems. 4. Point-in-Time (PIT) & Bridge Table Validation Since Data Vault is pattern-based, the first layer

Data Vault should allow for high-concurrency loading. Verify that a new Satellite record is created

Insert a record with a modified attribute. Verify that a new Satellite record is created with the updated data while the old record remains (historical tracking).

Test the performance of PIT tables; they should significantly speed up the joining of multiple Satellites.

The "Information Mart" layer is where users actually query the data.

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