About Metadata


Meta Data describes characteristics of PowerOLAP objects used for database architecture. Meta Data facilitates searching, management and linking database content, thereby enabling users to assemble “reusable” database objects. The minimum Meta Data components required to describe a PowerOLAP model are: Dimensions, Members, Dimension Hierarchies and Cubes. Expanded models may include Weighted Members, Alias Groups, Property Groups, and Cube Formulas.

The natural step-by-step construction of a PowerOLAP database model is demonstrated in the following diagram:

Constructing Dimensions is the first step in developing a multidimensional PowerOLAP model. Dimensions are lists of related things, like Salesperson or Account. Defining which Dimensions will meet your organization’s reporting and analysis needs is key to the creation of an optimal database. Some organizations may only need a 3- or 4-dimensional model (Month, Region, Salesperson and Account, for example) while others may need a dozen. Note that Dimensions do not contain or store data; they are made up of Hierarchies of Members. Putting the Dimension members into Hierarchies defines the axes within the database to store data. The resultant axes define the shape of a Cube. Fact Data is stored at Dimension Member intersection points on these axes within the Cube.

A simple example of a Dimension may be Month, which would list months of the year as separate Members along the axis of the Month dimension. Members of the Months dimension might be January, February, March, etc. Additional examples of Dimensions and their Members appear in the following table.

Examples of 5 different Dimensions and their 5 Members appear in the following figure:







Member 1





James Taylor

Member 2

Cost of Sales




Jill Fraser

Member 3

Gross Profit




Dawn Gilbert

Member 4

Gross Margin




Ron Gifford

Member 5





Hugh Mather



Note that there is no absolute limit to the number of Dimensions, Members or Cubes that you can create within a PowerOLAP database. You may, however, be limited by the available memory in your computer.

Given this background on Meta Data, we will next turn our attention to working with Dimensions themselves—how to model Dimensions and their Members.



When Dimensions are created via OLAP Exchange® (See OLAP Exchange section) many elements will be created based on the logic of underlying relational tables. Thus, for example, a Regions dimension would include all geographical areas where a company does business, as noted in a Field within a relational table. The Members would be supplied by that table, and potentially, a Hierarchy might also be possible, based on other Field information. Even so, the following information is critical to absorb because, whether Dimensions are created by OLAP Exchange® or not, they can be further modeled as explained in the following pages. Furthermore, PowerOLAP® allows you to add other Dimensions to those created by OLAP Exchange®—i.e., you are not limited to Dimensions sourced from underlying relational database tables.