What techniques help capture data lineage for a new Clarity module?

What techniques help capture data lineage for a new Clarity module?

• A. Lineage is unnecessary with surrogate keys.
• B. Only rely on vendor manifests.
• C. Document lineage after data retirement.
• D. Tag fields with source_system, source_table, transformation logic; maintain a lineage matrix and documentation.

Answer: (D)

Data lineage is about making provenance visible from source to destination, including how each value is transformed along the way. For a new Clarity module, the strongest approach is to tag each field with metadata that captures its origin and how it was derived: note the source_system, the source_table, and the transformation logic that produced the field. This field-level tagging creates precise traceability for every data element. Along with tagging, maintain a lineage matrix that explicitly maps sources to their downstream targets, showing dependencies across the data flows. Pair this with thorough documentation that explains data sources, transformation rules, quality checks, and any special handling. Together, the tags, the lineage matrix, and the documentation provide a clear, auditable view of how data moves and changes, which is essential for impact analysis, debugging, and governance. Surrogate keys don’t reveal provenance on their own and can mask where data originated or how it was transformed. Vendor manifests may capture some sources, but they’re often incomplete or out of date and don’t cover all transformations. Documenting lineage after retirement misses the opportunity to analyze changes, assess impact, and ensure ongoing data quality.

Data lineage is about making provenance visible from source to destination, including how each value is transformed along the way. For a new Clarity module, the strongest approach is to tag each field with metadata that captures its origin and how it was derived: note the source_system, the source_table, and the transformation logic that produced the field. This field-level tagging creates precise traceability for every data element.

Along with tagging, maintain a lineage matrix that explicitly maps sources to their downstream targets, showing dependencies across the data flows. Pair this with thorough documentation that explains data sources, transformation rules, quality checks, and any special handling. Together, the tags, the lineage matrix, and the documentation provide a clear, auditable view of how data moves and changes, which is essential for impact analysis, debugging, and governance.

Surrogate keys don’t reveal provenance on their own and can mask where data originated or how it was transformed. Vendor manifests may capture some sources, but they’re often incomplete or out of date and don’t cover all transformations. Documenting lineage after retirement misses the opportunity to analyze changes, assess impact, and ensure ongoing data quality.