By understanding the need for data governance and its potential consequences, organizations can establish robust frameworks that ensure data quality and integrity.

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On the other hand, AI is a branch of computer science that aims to create systems capable of performing tasks that require human intelligence, such as learning, reasoning, problem-solving, and language understanding.

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They enable data-driven decision-making, predictive analysis, operational efficiency, personalized customer experiences, risk management, cost savings, and innovation.

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Data governance can be defined as the management framework that ensures the quality, integrity, and security of an organization’s data assets.

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Without proper governance practices in place to monitor data quality at every stage — from collection to storage to analysis — organizations risk making flawed decisions based on unreliable or outdated information.

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