DBT handles data lineage and auditing by tracking the history of transformations and changes to your data, allowing you to understand where data comes from, how it was transformed, and who made changes to it.
Data lineage in DBT is maintained through the use of materialized views, which are a type of database table that stores the result of a SQL query. When a DBT model is run, a materialized view is generated in the target database that represents the result of the transformation. The materialized view contains information about the data lineage, such as the source tables and columns used, and the transformations applied.
Auditing in DBT is performed by tracking changes to the models and their corresponding materialized views. DBT keeps a record of every run of each model, including information about who ran it, when it was run, and what changes were made. This information can be used to perform auditing and compliance checks, as well as to revert changes if necessary.
The “dbt docs generate” command can be used to generate a documentation site that includes information about the data lineage and auditing information for each model and materialized view. The documentation site can be used to track the history of transformations and changes to your data, helping you maintain data quality and comply with data governance and auditing requirements.
Here’s an example of how DBT handles data lineage and auditing:
- A data analyst creates a new DBT model to transform data from a source table called “orders” into a materialized view called “orders_transformed”.
- The analyst runs the model, which generates the “orders_transformed” materialized view in the target database. The materialized view contains information about the data lineage, including the source table and columns used to create the view and the transformations that were applied.
- The analyst makes a change to the model and re-runs it. DBT tracks this change and updates the “orders_transformed” materialized view to reflect the new transformation.
- The analyst wants to know the history of changes made to the “orders_transformed” materialized view. They use the ” dbt docs generate ” command to generate a documentation site, which includes information about the data lineage and auditing information for each model and materialized view.
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