What outcomes are related to data architecture?

What outcomes are related to data architecture?

• A. High-level integrated designs
• B. Short-term marketing strategies
• C. Employee performance metrics
• D. Cost-cutting measures

Answer: (A)

The choice that relates to data architecture is centered around the development of high-level integrated designs. Data architecture fundamentally involves structuring an organization’s data assets in a coherent framework that aligns with its strategic goals. It encompasses the models, policies, rules, and standards that govern data collection, storage, protection, and usage. High-level integrated designs provide a blueprint for organizing data systems, ensuring that different components work together seamlessly and effectively. This integration supports data governance and facilitates better decision-making across the organization by creating a cohesive data landscape. In contrast, short-term marketing strategies, employee performance metrics, and cost-cutting measures do not directly address the infrastructural and design considerations inherent in data architecture. While these elements are important for business operations, they focus on tactical outcomes rather than the foundational structures and frameworks that data architecture is concerned with.

The choice that relates to data architecture is centered around the development of high-level integrated designs. Data architecture fundamentally involves structuring an organization’s data assets in a coherent framework that aligns with its strategic goals. It encompasses the models, policies, rules, and standards that govern data collection, storage, protection, and usage.

High-level integrated designs provide a blueprint for organizing data systems, ensuring that different components work together seamlessly and effectively. This integration supports data governance and facilitates better decision-making across the organization by creating a cohesive data landscape.

In contrast, short-term marketing strategies, employee performance metrics, and cost-cutting measures do not directly address the infrastructural and design considerations inherent in data architecture. While these elements are important for business operations, they focus on tactical outcomes rather than the foundational structures and frameworks that data architecture is concerned with.