Data Management
“The beginning of wisdom is the definition of terms.”
“The beginning of wisdom is the definition of terms.”
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Data Lineage is metadata that identifies the sources of data and the transformations through which it has passed up to the point of applying. (DAMA-NL, 2020)
Other definitions:
Data lineage answers the 5 W’s of data:
Data chain
Phase | Activity |
---|---|
Plan | * Define the scope * Select a way to store the DL information, e.g., by an editor or in a DL tool * Collect the relevant metadata * Enter, change, or delete the metadata * “Stitch the nodes” |
Do | * Use the DL for its purpose |
Check | * Evaluate the effectiveness of the DL |
Act | * Adapt the DL * Maintain the DL |
Characteristic | Requirement |
---|---|
Completeness | DL is complete regarding the scope. |
Maintainability | DL can be maintained efficiently. |
Clarity | DL can be interpreted easily (zooming, filtering) |
Subtypes of data lineage are:
Legislation requires the Valencia bank to report monthly to its regulator, the central bank. The regulator, however, also wants to know how these reports have been produced and where the data comes from. This is to assess the quality of the data.
Because the reports are generated by complex data flows, the bank decides to apply data lineage to map these flows and make them visible. It soon turned out that fields with the same meaning had different names in the systems involved.
Nevertheless, it was possible to link the fields and it became clear where the reported data came from. The bank can now satisfactorily inform the supervisor about the origin of the reported data. A data steward is made responsible for the maintenance of the data lineage in the tool, so that the metadata is kept up to date.
Data lineage also proves to be useful when making changes to the systems. The impact of changes in the systems downstream can be understood more quickly.