A single-dimensional data classification uses one dimension to divide the application data into segments.
Use a single-dimensional data classification when you want to create segments for application data in one way, such as by year or quarter. Single-dimensional data classifications often use the time dimension.
For example, you manage three years of application data that you want to divide into segments by quarter. You create a time dimension and select range as the dimension type and date as the datatype. When you run the segmentation policy the ILM Engine creates 13 segments, one for each quarter and one default segment. The data in the default segment includes all of the data that does not meet the requirements for a segment, such as transactions that are still active. The default segment also includes new transactional data.