Which attribute is essential to data integrity across its lifecycle?

• A. Latency
• B. Volume
• C. Format consistency
• D. Accuracy

Answer: (D)

Data integrity across its lifecycle rests on accuracy—the data must reflect true values and stay correct as it moves from collection to storage, processing, analysis, and use. Accuracy matters most because it directly determines whether the data represents reality. If values are incorrect, decisions, insights, and actions derived from the data will be faulty, even if other aspects of data management are strong.

Even when data arrives quickly (latency), exists in large quantities (volume), or is stored and shared in a consistent format (format consistency), inaccuracies can propagate through systems and lead to misguided results. For example, a price error in a sales record will skew revenue reporting regardless of how fast updates occur or how uniform the data format is.

Preserving accuracy involves validation, reconciliation against trusted sources, error checking, cleansing, and maintaining a clear audit trail so that the data remains a correct reflection of reality throughout its life.