Instructions and covered skills
Read each question carefully before selecting a response. Focus on the stated systems, fields, transformations, and business outputs. Do not assume undocumented relationships or controls. Choose the response that best reflects a maintainable lineage practice. Stay focused and avoid distractions while working through the test. Turn off notifications and reserve enough uninterrupted time to review each scenario.
Key Areas
This test evaluates the ability to map and interpret how data moves across operational sources, ingestion processes, transformation layers, curated datasets, semantic models, dashboards, extracts, and regulatory outputs. Candidates should be able to distinguish dataset-level relationships from column-level relationships and identify when more detailed field tracing is necessary. They should understand how to document source systems, source objects, target objects, transformation logic, owners, refresh dependencies, and business definitions in a lineage record.
Strong performance requires practical impact-analysis judgment. This includes tracing a proposed source-field change through pipelines and derived assets, identifying reports or metrics affected by a failed transformation, and separating direct dependencies from downstream dependencies. The test also covers lineage for joins, aggregations, filters, unions, calculated fields, reference-data lookups, and manual inputs. Attention is given to preserving the relationship between technical metadata and the business meaning of a metric.
Candidates should recognize that lineage is not a one-time diagram. Useful records have accountable owners, validation evidence, review triggers, and a process for reflecting changes. They should also understand how lineage supports incident investigation, change approval, audit requests, data-access review, and trust in published information.
Recommended Preparation
Review examples of data catalogs, lineage diagrams, pipeline documentation, and impact-assessment records used in analytics or data-platform environments. Practice tracing a business metric backward from a dashboard to a semantic measure, curated table, transformation job, and source field. Then trace a source change forward to the models, reports, extracts, and operational processes that consume it.
Study common transformation patterns, including field renaming, type conversion, deduplication, aggregation, joins, filtering, derived calculations, and reference-data enrichment. Practice writing lineage statements that name the source, target, logic, schedule, and accountable role without relying on undocumented assumptions. When reviewing a lineage map, look for missing manual steps, ambiguous ownership, hidden spreadsheet dependencies, and stale references after system changes.