Data drift refers to changes in?

• A. Changes in input data storage location
• B. Changes in input data distribution over time
• C. Changes in data labeling standards
• D. Changes in processing speed

Answer: (B)

Data drift is about changes in the distribution of input data over time. When the data fed into a model shifts its statistical properties—such as averages, variances, or how features relate to each other—the model’s predictions can become less accurate because it was trained on a different distribution. This is different from where data is stored, changes in how data is labeled, or changes in how fast processing happens. Monitoring for such distribution changes and updating or retraining the model helps maintain performance.