Data Governance and Standards Flashcards

What is a business glossary and why is it important in data modeling?

Answer: An authoritative list of business terms with agreed definitions used consistently across the organization

A business glossary provides standard definitions for business terms, ensuring that data modelers, developers, and business users all mean the same thing when they use key terms.

What is data masking and when is it applied in a governed data environment?

Answer: Replacing sensitive data values with realistic but fictitious substitutes to protect privacy in non-production environments

Data masking substitutes sensitive production data (like SSNs or credit card numbers) with realistic fictitious values, allowing development and testing without exposing real personal data.

What is a data standard in the context of enterprise data governance?

Answer: An agreed-upon rule or format that data must conform to — such as date formats, code values, or naming patterns — enforced across systems

Data standards define mandatory formats, code sets, naming rules, and quality thresholds that all data systems must conform to, enabling integration and consistent interpretation.

In data governance, what is the role of a data governance council?

Answer: To serve as a cross-functional decision-making body that sets data policies, resolves conflicts, and prioritizes data initiatives

A data governance council brings together senior stakeholders from business and IT to establish data policies, resolve disputes about data ownership, and prioritize governance initiatives.

What does 'data sovereignty' mean and why does it affect physical data modeling decisions?

Answer: The legal concept that data is subject to the laws of the country where it is stored, affecting where data can physically reside

Data sovereignty means data is governed by the laws of the country it is stored in, requiring physical models to implement region-specific data stores for compliance with local regulations.

What is the purpose of a data model review process in a governed organization?

Answer: To ensure proposed data model changes conform to standards, don't break integrations, and are documented before implementation

A formal data model review process validates that changes meet naming standards, maintain data quality constraints, don't break downstream systems, and are properly documented in the data dictionary.