What principle emphasizes accountability in data governance within MDM?

What principle emphasizes accountability in data governance within MDM?

• A. Quality
• B. Stewardship
• C. Controlled Change
• D. Ownership

Answer: (D)

The principle that emphasizes accountability in data governance within Master Data Management (MDM) is ownership. Ownership refers to the assignment of clear responsibility for data, ensuring that individuals or teams are accountable for the quality, usage, and integrity of the data they manage. When data ownership is clearly defined, it fosters a culture of stewardship and responsibility, leading to better data governance practices. By establishing ownership, organizations can ensure that there are designated individuals who understand the significance of the data, manage its quality, and make decisions regarding its use. This accountability is crucial in addressing data inconsistencies, ensuring compliance with data policies, and ultimately driving the success of MDM initiatives. Other principles like stewardship focus on the care and oversight of data management processes but may not inherently carry the same level of personal accountability that ownership does. Quality emphasizes the standards that data must meet, while controlled change relates to managing modifications in data processes. While all principles contribute to effective data governance, ownership is the cornerstone for establishing a culture of accountability and responsibility.

The principle that emphasizes accountability in data governance within Master Data Management (MDM) is ownership. Ownership refers to the assignment of clear responsibility for data, ensuring that individuals or teams are accountable for the quality, usage, and integrity of the data they manage. When data ownership is clearly defined, it fosters a culture of stewardship and responsibility, leading to better data governance practices.

By establishing ownership, organizations can ensure that there are designated individuals who understand the significance of the data, manage its quality, and make decisions regarding its use. This accountability is crucial in addressing data inconsistencies, ensuring compliance with data policies, and ultimately driving the success of MDM initiatives.

Other principles like stewardship focus on the care and oversight of data management processes but may not inherently carry the same level of personal accountability that ownership does. Quality emphasizes the standards that data must meet, while controlled change relates to managing modifications in data processes. While all principles contribute to effective data governance, ownership is the cornerstone for establishing a culture of accountability and responsibility.