DA0-002 Data Governance Practice Question
A multinational corporation is implementing a data governance program. The Chief Data Officer wants to ensure that data quality issues are detected and resolved promptly across all business units. Which combination of roles and responsibilities is most appropriate for this goal?
⚠ Common exam trap
The trap here is assuming that centralizing all data quality work in IT or fully decentralizing without oversight will be sufficient.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Assign data stewards in each business unit to monitor quality metrics and escalate issues to a central data governance council.
A federated data governance model with data stewards embedded in business units and a central council for oversight is widely recognized as effective. Stewards handle domain-specific quality issues, while the council sets standards and resolves cross-functional conflicts. This structure ensures both local responsiveness and enterprise alignment, which is critical for a multinational corporation with diverse business units.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Outsource data quality monitoring to a third-party vendor to gain external expertise.
Why it's wrong here
Outsourcing can provide specialized skills, but it does not replace internal accountability. Data stewards within the business are needed to interpret issues and drive resolution. A third party may lack the deep business context required to prioritize and remediate quality problems effectively.
- ✗
Centralize all data quality responsibilities within the IT department to ensure consistent technical standards.
Why it's wrong here
While IT plays a key role in implementing data quality tools, business units understand the data's context and usage. Centralizing solely in IT often leads to a disconnect between technical fixes and business needs. It also creates bottlenecks and reduces business ownership of data quality.
- ✗
Require each business unit to manage data quality independently without central oversight.
Why it's wrong here
Independent management without central coordination leads to inconsistent standards, duplicated efforts, and conflicting definitions. A governance council is needed to establish common policies, metrics, and escalation paths. Without it, the organization cannot achieve enterprise-wide data quality.
- ✓
Assign data stewards in each business unit to monitor quality metrics and escalate issues to a central data governance council.
Why this is correct
Data stewards are responsible for day-to-day data quality management within their domains. They monitor metrics, resolve issues, and escalate when necessary. A central council provides oversight and cross-functional coordination. This federated model balances local accountability with enterprise-wide consistency, which is essential for a multinational corporation.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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