Define "data integrity."

Enhance your skills for the Gramling Business Analytics Exam. Prepare with flashcards and multiple-choice questions, each offering hints and explanations. Gear up for your exam!

Data integrity refers to the accuracy and consistency of data throughout its lifecycle. This concept is crucial in ensuring that information remains reliable and trustworthy from the moment it is collected, stored, processed, analyzed, and shared. Maintaining data integrity involves applying various practices, such as validating and cleansing data, ensuring proper access controls, and implementing robust security measures to prevent unauthorized changes. When data integrity is upheld, organizations can confidently base their decisions and insights on high-quality, dependable information.

In contrast, the other choices focus on different aspects of data management, such as accessibility, processing speed, and cost efficiency, which, while important, do not define the core concept of data integrity. The emphasis is squarely on ensuring that the data remains correct and unchanged over time, which is the essence of what data integrity is about.

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