Which of the following best describes a data-centric organization?

Which of the following best describes a data-centric organization?

• A. It avoids using data for decision-making
• B. It values data throughout its lifecycle
• C. Data management is isolated from business operations
• D. Data is managed only during project development

Answer: (B)

A data-centric organization is best described by its emphasis on valuing data throughout its lifecycle. This approach recognizes data not just as a byproduct of business processes but as a critical asset that influences every aspect of decision-making and strategy. In such organizations, data is consistently collected, maintained, and leveraged to improve various functions, driving better insights and more informed decisions. Valuing data throughout its lifecycle involves comprehensive practices including data governance, quality management, and integration, ensuring that data remains relevant, accurate, and available for all stakeholders. It highlights the importance of data from its creation, through usage, and into eventual archival or deletion, demonstrating a holistic commitment to managing and utilizing data effectively. This perspective sharply contrasts with the other options. For instance, avoiding the use of data for decision-making undermines the entire premise of being data-centric. Similarly, isolating data management from business operations disrupts the potential for data to inform and guide everyday practices, while managing data only during project development ignores the ongoing need for data management throughout its entire lifecycle. Thus, focusing on the value of data across its lifecycle encapsulates the essence of what it means to be a data-centric organization.

A data-centric organization is best described by its emphasis on valuing data throughout its lifecycle. This approach recognizes data not just as a byproduct of business processes but as a critical asset that influences every aspect of decision-making and strategy. In such organizations, data is consistently collected, maintained, and leveraged to improve various functions, driving better insights and more informed decisions.

Valuing data throughout its lifecycle involves comprehensive practices including data governance, quality management, and integration, ensuring that data remains relevant, accurate, and available for all stakeholders. It highlights the importance of data from its creation, through usage, and into eventual archival or deletion, demonstrating a holistic commitment to managing and utilizing data effectively.

This perspective sharply contrasts with the other options. For instance, avoiding the use of data for decision-making undermines the entire premise of being data-centric. Similarly, isolating data management from business operations disrupts the potential for data to inform and guide everyday practices, while managing data only during project development ignores the ongoing need for data management throughout its entire lifecycle. Thus, focusing on the value of data across its lifecycle encapsulates the essence of what it means to be a data-centric organization.