Which concept is about establishing clear data usage policies and ensuring data aligns with organizational goals?

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Multiple Choice

Which concept is about establishing clear data usage policies and ensuring data aligns with organizational goals?

Explanation:
Data governance centers on setting clear policies for how data is used, who owns it, and the standards it must meet, all to ensure data assets support the organization’s goals. It provides the framework for accountability, decision rights, and controls across the data lifecycle—collection, storage, processing, sharing, and retirement—while addressing quality, privacy, security, and compliance. When policies and responsibilities are well defined, data aligns with strategic objectives and regulatory requirements, enabling consistent, trustworthy use of data across the organization. Leading indicators are forward-looking metrics used to anticipate performance, not a policy framework. Data loss describes an event where data becomes unavailable or missing, not the governance structure that guides data use. Training data issues refer to problems in the data used to train models, such as quality or bias, rather than the overarching policies and governance of data assets.

Data governance centers on setting clear policies for how data is used, who owns it, and the standards it must meet, all to ensure data assets support the organization’s goals. It provides the framework for accountability, decision rights, and controls across the data lifecycle—collection, storage, processing, sharing, and retirement—while addressing quality, privacy, security, and compliance. When policies and responsibilities are well defined, data aligns with strategic objectives and regulatory requirements, enabling consistent, trustworthy use of data across the organization.

Leading indicators are forward-looking metrics used to anticipate performance, not a policy framework. Data loss describes an event where data becomes unavailable or missing, not the governance structure that guides data use. Training data issues refer to problems in the data used to train models, such as quality or bias, rather than the overarching policies and governance of data assets.

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