Siebel Analytics Server Administration Guide > Working in a Repository's Business Model and Mapping Layer > Business Model and Mapping Layer Objects >

Working with Dimensions


Dimensions are categories of attributes by which the business is defined. Common dimensions are time periods, products, markets, customers, suppliers, promotion conditions, raw materials, manufacturing plants, transportation methods, media types, and time of day. Within a given dimension, there may be many attributes. For example, the time period dimension could contain the attributes day, week, month, quarter, and year. Exactly what attributes a dimension contains depends on the way the business is analyzed.

Dimensions are organized into hierarchies. These hierarchies express the organizational rules set up by your business. Hierarchies provide the metadata needed for the Siebel Analytics Server to drill down within and across dimensions to get less summarized views of the data.

All of the objects within a dimension are used for metadata purposes only. End users do not see the dimensions themselves. The metadata from the dimensional hierarchies is used to perform aggregate navigation, to set up dimension-specific aggregation rules (see Dimension-Specific Aggregation Rules), and to configure level-based measure calculations (see Level-Based Measure Calculations), and to determine what attributes are shown when Siebel Analytics Web users drill down in their data requests.

These hierarchy definitions must be specific to the business model—one model may be set up where weeks roll up into a year, and another where they do not. For example, in a model where weeks roll up into a year, it is implied that each week has exactly one year associated with it; this may not hold true for calendar weeks, where the same week could span two years. Some hierarchies might require multiple elements to roll up, as when the combination of month and year roll up into exactly one quarter. The Siebel Analytics Server allows you to define the hierarchy definitions for your particular business, however complex, assuring that analyses will conform to your business definitions.

Each dimension can have one or more hierarchies. Within each hierarchy is one or more levels, and each level has one or more attributes associated with it. Each dimension can be associated with attributes from just one logical dimension table (plus level-based measures from the logical fact tables).

NOTE:  If the logical table with which a dimension is associated has a foreign key defined, then the key column of the logical table must be included at the lowest level of the dimension.


 Siebel Analytics Server Administration Guide 
 Published: 23 June 2003