How do you document data lineage?

Great outline on the first step in documenting data lineage. To summarize and add to what you've mentioned: 1?? Identify Data Sources: Could be internal/external, structured/unstructured like databases, files, APIs, etc. 2?? Identify Data Targets: These could be data warehouses, data lakes, dashboards, or reports. 3?? Document Details: Note the name, location, owner, and description for each source and target. 4?? Frequency & Format: Log the frequency, format, and method of data ingestion or extraction. Including these details ensures a comprehensive approach to data lineage documentation, making future analysis and troubleshooting much more efficient. Like if you found helpful ??

You can document data lineage through a combination of specialized software tools and manual mapping. These tools automatically trace the flow of data from its origin through various transformations, capturing metadata at each stage. You then can supplement by manual documentation to provide context. The finalized lineage is then shown in flowcharts and stored in a centralized metadata repository for easy access and governance.

I would think one of the first steps is to understand who will be using the lineage and for what purpose. This would let us know what type of data lineage is required i.e. Coarse grained lineage vs fine grain lineage. This would drive the amount of effort required for the other steps. For example, Coarse-grained lineage is more useful for business users who don't need to see technical details. While fine grain lineage goes deeper into the data flow and shows the details of transformations applied to data.

By having a clear understanding of data lineage, organizations can perform impact analysis to assess how changes or issues in one part of the data pipeline affect downstream processes or reports. So it is inter linked between data-lineage and most of impact analysis team does [in case of missing official data lineage].

In addition to identifying sources and targets, make sure to ask to your IT peers if there is an existing inventory of applications, this would enable a "coarse grain" baseline of potential sources and targets, this step would potentially bring additional metadata relevant for your lineage strategy (such as custodians, database types, etc.) Along with your sources/targets, define a catalogue of attributes to use as tags (internal/external, structured/unstructured, full/delta, monthly/weekly/daily/stream)

Before starting the mapping of the data flows and transformations, one should first define/update/maintain the data dictionaries. In the data dictionaries, we have the relationships, meanings, data types, etc. of the data elements. Knowing these helps us to match and define proper filtering, cleansing, enriching, etc. of the data from source to target.

Depending on the tech stack offered by your data management professionals, make sure to identify the available metadata provided by the ETL/ELT or data integration platforms, ideally you should be able to enrich on top of the metadata collected with the transformation/derivation logic needed from your productive pipelines.

I recommend defining data elements prior to the data lineage. Without understanding the data elements, you can't be completely confident that your data lineage is accurate. For instance, if you map "customer start date" to "customer start date" purely because the names match, you might miss the fact that "customer start date" in the target was defined as something different starting than in the source.

This step represent the most challenging but with greater value for your data community, by enabling a visual representation of your data flows you provide an standardize mechanism to explore data dependencies and easy to read for any role. Based on the size of your operation, make sure to find a balanced detail of lineage, you would want to avoid an enormous amount of lineage diagrams to maintain if your budget is limited; also, explore free/open source solutions (SQL parser) that would enable easier updates.