: What strategies are there to document data lineage and keep it updated with a minimum amount of maintenance? Quickly communicating data lineage to other stakeholders in our organization has become

Quickly communicating data lineage to other stakeholders in our organization has become increasingly difficult as we scale.

What are effective strategies to address this and keep it maintained?

An example would be customer data that is stored in a data warehouse, processed in various ways, and used for analysis and reporting. The audience would be members of the business intelligence and analytics teams as well as product managers. The data lineage can change as developers add or modify the code.

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@Gonzalez219

As your question is fairly general, this answer is too.

I'd insert the ETL process itself into the target database. As you have on-site developers this will have to be included in your extraction development. Best add a bit of architecture description and versioning as well to serve the level of understanding of your consumers.

When going after this I'd include a similar step in the actual extraction run process; even a straightforward run-date and field for comments can be worth gold when attempting to generate trends a year hence.

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: What strategies are there to document data lineage and keep it updated with a minimum amount of maintenance? Quickly communicating data lineage to other stakeholders in our organization has become

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