In data mining, veracity refers to what?

• A. The quality of the data collected by the organizations
• B. The speed of data processing
• C. The number of data sources
• D. The accuracy of models

Answer: (A)

Veracity in data mining is about how trustworthy and reliable the data are for analysis. It encompasses data quality aspects like accuracy, completeness, consistency, and freedom from noise or bias. When data have high veracity, the insights and models built from them are more trustworthy; when veracity is low, even strong techniques can produce misleading results because the data themselves are not dependable.

This is why the best choice is that veracity concerns the quality of the data collected by organizations. It isn’t about how fast data are processed, how many sources exist, or how accurate the models are—the latter depends in part on data quality but is not what veracity describes.