Which artifact is a core artifact of data governance?

Prepare for the CMPE Organizational Governance Test with flashcards and multiple choice questions, complete with hints and explanations. Get ready to excel in your exam!

Multiple Choice

Which artifact is a core artifact of data governance?

Explanation:
In data governance, the artifacts you rely on are the documents and records that spell out how data is managed, who owns it, and how quality and visibility are ensured across the organization. The strongest artifact is a collection that includes the data policy, data stewardship assignments, data lineage, data quality metrics, and a data catalog. The policy sets the rules and standards for data usage and management. Stewardship assignments declare who is responsible for each data asset, ensuring accountability. Data lineage traces data from its source through transformations to its final state, which is essential for impact analysis and trust. Data quality metrics define how quality is measured and monitored, guiding improvement efforts. The data catalog inventories data assets and their metadata, making data discoverable and governable. The other choices miss essential governance elements: infrastructure diagrams describe technical setup rather than governance decisions; a backup schedule is about operational continuity, not governance structure; an access control matrix focuses on permissions but without the broader governance framework, it falls short of guiding governance of data assets.

In data governance, the artifacts you rely on are the documents and records that spell out how data is managed, who owns it, and how quality and visibility are ensured across the organization. The strongest artifact is a collection that includes the data policy, data stewardship assignments, data lineage, data quality metrics, and a data catalog.

The policy sets the rules and standards for data usage and management. Stewardship assignments declare who is responsible for each data asset, ensuring accountability. Data lineage traces data from its source through transformations to its final state, which is essential for impact analysis and trust. Data quality metrics define how quality is measured and monitored, guiding improvement efforts. The data catalog inventories data assets and their metadata, making data discoverable and governable.

The other choices miss essential governance elements: infrastructure diagrams describe technical setup rather than governance decisions; a backup schedule is about operational continuity, not governance structure; an access control matrix focuses on permissions but without the broader governance framework, it falls short of guiding governance of data assets.

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