A similar concept to data banding, derivative data allows analysts to create additional dimensions from existing data. This additive information is perfectly suited for the kinds of analysis in Emcien.
Example 1: If each transaction includes a specific location, either address, GPS coordinates, or even a state, an analyst could derive additional information by creating additional columns. This data could be used to add regions or time zones to the data set, giving the software additional opportunities to find patterns.
Example 2: In cases where dates are included in the data, it can be beneficial to derive a day of the week attribute from the date value. Patterns may be detected on days of the week more than days of the year.
Example 3: When data contains date and time at a very granular level it can be effective to derive an attribute to create larger groupings of events or usage. For example analysis of web traffic, understand the patterns for different periods of the day.