What does the delta transformation calculate in a dataset?

The delta transformation is designed to capture the change in a measure over time, essentially focusing on how the value of that measure evolves as time progresses. In the context of sorted data, it emphasizes the differences between consecutive values, which allows for a precise understanding of trends, patterns, and fluctuations.

By calculating the change of a measure over time, the delta transformation provides critical insights for analytics, such as identifying growth rates, declines, or stability in a given metric. This is particularly useful in fields like finance, sales, or performance measurement, where understanding these changes can inform strategic decision-making.

Other options, while related to numerical analysis, do not capture this specific concept of change:

• The total sum of a measure over time aggregates values but does not provide insight into how they change.

• The average of all measures gives a general overview, but again, it lacks the focus on change.

• The maximum value of a measure simply identifies the peak without addressing the dynamics of variation over time.

Thus, the correct answer highlights the essential function of delta transformation in analyzing time-dependent changes within datasets.