SSAS: Concept Grooming

Dimension Objects

Original

A simple Dimension object is composed of basic information, attributes, and hierarchies.

Basic information includes the name of the dimension, the type of the dimension, the data source, the storage mode, and OT Hers.

Attributes Define the actual data in the dimension.

Attributes does not necessarily belong to a hierarchy, but hierarchies is built from Attributes.

A hierarchy creates ordered lists of levels, and defines the ways a user can explore the dimension.

• Attributes and Attribute hierarchies
• Attribute relationships

Original

Dimensions is a fundamental component of cubes.

Dimensions organize data with relation to a area of interest, such as customers, stores, or employees, to users.

Dimensions in Analysis Services contain attributes , correspond to columns in dimension tables.

These attributes appear as attribute hierarchies and can be organized to user-defined hierarchies, or can be de Fined as Parent-child hierarchies based on columns in the underlying dimension table.

hierarchies is used to organize measures that is contained in a cube.

Cube Objects

Original

A simple Cube object is composed of:basic information, dimensions, and measure groups .

Basic Information includes the name of the cube, the default measure of the cube, the data source, the storage mo De, and others.

The Dimensions collection contains the actual set of Dimensions used in the cube from the database Dimensions colection.

All dimensions has the defined in the Dimensions collection of the database before being referenced in the cube.

Private dimensions is not available in Microsoft SQL Server analysis Services.

Measure Groups is sets of measures in the cube.

A measure group is a collection of measures, which has a common data source view and a common set of dimensions.

A measure group is the unit of process for measures; Measure groups can is processed individually and then browsed.

• Actions (Analysis services-multidimensional Data)
• Aggregations and Aggregation Designs
• Calculations
• Cube Cells (Analysis services-multidimensional Data)
• Cube properties-multidimensional Model Programming
• Cube Storage (Analysis services-multidimensional Data)
• Cube Translations
• Dimension relationships
• Key performance Indicators (KPIs) in multidimensional Models
• Measures and Measure Groups

SSAS: Concept Grooming