Why should an organization conform to a standard data governance framework?

Why should an organization conform to a standard data governance framework?

• A. To ensure that an organization can manage data in a consistent manner and ensure that data is trustworthy.
• B. To maximize data silos and fragmentation.
• C. To reduce the amount of data collected.
• D. To increase complexity of data access.

Answer: (A)

Conforming to a standard data governance framework centers on managing data consistently and ensuring it is trustworthy. By defining who owns data, who can use it, what quality standards apply, and how data is stored, secured, and retired, the framework creates uniform rules and processes across the organization. This coherence makes data more accurate, complete, and discoverable, enabling reliable reporting, better decision making, and compliance with laws and policies. When data is treated as a governed asset rather than a collection of isolated sources, trust grows and analytics become more dependable. The other options miss the mark because they describe outcomes that governance aims to avoid or counteract: maximizing silos would reduce data sharing and consistency; reducing the amount of data collected is not the goal of governance—it’s about governing what exists and how it’s used; increasing data access complexity would undermine usability and trust, whereas a good framework clarifies and controls access to streamline legitimate use.

Conforming to a standard data governance framework centers on managing data consistently and ensuring it is trustworthy. By defining who owns data, who can use it, what quality standards apply, and how data is stored, secured, and retired, the framework creates uniform rules and processes across the organization. This coherence makes data more accurate, complete, and discoverable, enabling reliable reporting, better decision making, and compliance with laws and policies. When data is treated as a governed asset rather than a collection of isolated sources, trust grows and analytics become more dependable.

The other options miss the mark because they describe outcomes that governance aims to avoid or counteract: maximizing silos would reduce data sharing and consistency; reducing the amount of data collected is not the goal of governance—it’s about governing what exists and how it’s used; increasing data access complexity would undermine usability and trust, whereas a good framework clarifies and controls access to streamline legitimate use.