The data used in creating measures and attributes pulled from your contact center’s database are organized into datasets. In Historical Reporting, a dataset is a basic organizational unit for these data. It is a set of related measures, a set of attributes, or a set of both.
Datasets are connected to one another to create exclusive relationships. For example, Dataset A is connected to Dataset B, but is not connected to Dataset C. Dataset B, on the other hand, is connected to Dataset C. This means that A can interact with B but not with C and vice versa. However, B can interact with both A and C.
Try to imagine each dataset as boxes with data in them. Datasets connected to one another constitute a logical data model (LDM). The LDM in Historical Reporting is used to determine which data can interact with another data.
In Historical Reporting, there are two important datasets for data: segment and agent state. Some data are tagged and can be found under those categories, while some are not. When you drag a measure or an attribute to a section on the canvas, the data catalog will repopulate and only data compatible with the one on the canvas will appear in the catalog.
It is also important to understand the concept of the segment and agent state datasets so you don’t confuse compatible data with incompatible data when conceptualizing insights you want to create.