Interval Data

Interval data is a type of data where the difference between two values is meaningful and consistent, but there’s no true zero point, which means you can’t talk about one value being “twice” or “three times” as much as another. In the context of business intelligence and data analytics, consider interval data like the dates on a calendar or temperatures in degrees Celsius. We can say that March 21 is 90 days after December 21, or that 20 degrees is warmer than 10 degrees, but we can’t say it’s “twice as warm.”

This kind of data is really useful for businesses when they want to measure and analyze changes over time or establish a sequence. For example, they might use interval data to understand how customer satisfaction scores vary from one quarter to the next or to look at how the average delivery time for orders trends throughout the year. It helps to identify patterns and review performance within specific intervals.

Understanding interval data helps businesses make more accurate and nuanced decisions. Since the differences between data points are significant, businesses can use statistical methods to analyze trends and forecasts. This deeper level of analysis can be a key part of a company’s strategy to improve operations, marketing, and other areas that are vital to its success.