In data governance, which principle refers to the integration of data management into business processes?

In data governance, which principle refers to the integration of data management into business processes?

• A. Measured outcomes
• B. Embedded strategy
• C. Multi-layered execution
• D. Framework basis

Answer: (B)

The principle that refers to the integration of data management into business processes is known as embedded strategy. This concept highlights the importance of weaving data governance practices seamlessly into the day-to-day operations of an organization, ensuring that data management is not treated as a separate or siloed function but rather as an integral component of overall business strategy. An embedded strategy fosters a culture where data-driven decision-making is a norm, and where the quality, security, and availability of data are continuously monitored and maintained throughout all levels of the organization. This approach helps organizations better align their data initiatives with business objectives, enhancing both data usability and business performance. In contrast, the other options focus on different aspects of data governance. Measured outcomes pertain to the effectiveness of governance initiatives based on defined metrics, while multi-layered execution refers to the various levels at which data governance can be implemented across an organization. Framework basis typically refers to the foundational structures that guide data governance policies and practices but does not specifically address integration into business processes.

The principle that refers to the integration of data management into business processes is known as embedded strategy. This concept highlights the importance of weaving data governance practices seamlessly into the day-to-day operations of an organization, ensuring that data management is not treated as a separate or siloed function but rather as an integral component of overall business strategy.

An embedded strategy fosters a culture where data-driven decision-making is a norm, and where the quality, security, and availability of data are continuously monitored and maintained throughout all levels of the organization. This approach helps organizations better align their data initiatives with business objectives, enhancing both data usability and business performance.

In contrast, the other options focus on different aspects of data governance. Measured outcomes pertain to the effectiveness of governance initiatives based on defined metrics, while multi-layered execution refers to the various levels at which data governance can be implemented across an organization. Framework basis typically refers to the foundational structures that guide data governance policies and practices but does not specifically address integration into business processes.