# Introduction to Cubes

A cube is defined by its measures and dimensions. The measures and dimensions in a cube are derived from the tables and views in the data source view on which the cube is based, or which is generated from the measure and dimension definitions.

## Cube Example

The Imports cube contains two measures, Packages and Last, and three related dimensions, Route, Source, and Time.

The smaller alphanumeric values around the cube are the members of the dimensions. Example members are ground (member of the Route dimension), Africa (member of the Source dimension), and 1st quarter (member of the Time dimension).

### Measures

The values within the cube cells represent the two measures, Packages and Last. The Packages measure represents the number of imported packages, and the Sum function is used to aggregate the facts. The Last measure represents the date of receipt, and the Max function is used to aggregate the facts.

### Dimensions

The Route dimension represents the means by which the imports reach their destination. Members of this dimension include ground, nonground, air, sea, road, or rail. The Source dimension represents the locations where the imports are produced, such as Africa or Asia. The Time dimension represents the quarters and halves of a single year.

### Aggregates

Business users of a cube can determine the value of any measure for each member of every dimension, regardless of the level of the member within the dimension, because Analysis Services aggregates values at upper levels as needed. For example, the measure values in the preceding illustration can be aggregated according to a standard calendar hierarchy by using the Calendar Time hierachy in the Time dimension as illustrated in the following diagram.

In addition to aggregating measures by using a single dimension, you can aggregate measures by using combinations of members from different dimensions. This allows business users to evaluate measures in multiple dimensions simultaneously. For example, if a business user wants to analyze quarterly imports that arrived by air from the Eastern Hemisphere and Western Hemisphere, the business user can issue a query on the cube to retrieve the following dataset.

Packages Last

All Sources

Eastern Hemisphere

Western Hemisphere

All Sources

Eastern Hemisphere

Western Hemisphere

All Time

25110

6547

18563

Dec-29-99

Dec-22-99

Dec-29-99

1st half

11173

2977

8196

Jun-28-99

Jun-20-99

Jun-28-99

1st quarter

5108

1452

3656

Mar-30-99

Mar-19-99

Mar-30-99

2nd quarter

6065

1525

4540

Jun-28-99

Jun-20-99

Jun-28-99

2nd half

13937

3570

10367

Dec-29-99

Dec-22-99

Dec-29-99

3rd quarter

6119

1444

4675

Sep-30-99

Sep-18-99

Sep-30-99

4th quarter

7818

2126

5692

Dec-29-99

Dec-22-99

Dec-29-99

After a cube is defined, you can create new aggregations, or you can change existing aggregations to set options such as whether aggregations are precalculated during processing or calculated at query time. Related topic:Aggregations and Aggregation Designs (SSAS).

### Mapping Measures, Attributes, and Hierarchies

The measures, attributes, and hierarchies in the example cube are derived from the following columns in the cube's fact and dimension tables.

 Measure or attribute (level) Members Source table Source column Sample column value Packages measure Not applicable ImportsFactTable Packages 12 Last measure Not applicable ImportsFactTable Last May-03-99 Route Category level in Route dimension nonground,ground RouteDimensionTable Route_Category Nonground Route attribute in Route dimension air,sea,road,rail RouteDimensionTable Route Sea Hemisphere attribute in Source dimension Eastern Hemisphere,Western Hemisphere SourceDimensionTable Hemisphere Eastern Hemisphere Continent attribute in Source dimension Africa,Asia,AustraliaEurope,N. America,S. America SourceDimensionTable Continent Europe Half attribute in Time dimension 1st half,2nd half TimeDimensionTable Half 2nd half Quarter attribute in Time dimension 1st quarter,2nd quarter,3rd quarter,4th quarter TimeDimensionTable Quarter 3rd quarter

Data in a single cube cell is usually derived from multiple rows in the fact table. For example, the cube cell at the intersection of the air member, the Africa member, and the 1st quarter member contains a value that is derived by aggregating the following rows in the ImportsFactTable fact table.

 Import_ReceiptKey RouteKey SourceKey TimeKey Packages Last 3516987 1 6 1 15 Jan-10-99 3554790 1 6 1 40 Jan-19-99 3572673 1 6 1 34 Jan-27-99 3600974 1 6 1 45 Feb-02-99 3645541 1 6 1 20 Feb-09-99 3674906 1 6 1 36 Feb-17-99

In the preceding table, each row has the same values for the RouteKey, SourceKey, and TimeKey columns, indicating that these rows contribute to the same cube cell.

The example shown here represents a very simple cube, in that the cube has a single measure group, and all the dimension tables are joined to the fact table in a star schema. Another common schema is a snowflake schema, in which one or more dimension tables join to another dimension table, rather than joining directly to the fact table. Related topic:Dimensions (Analysis Services).

The example shown here contains only a single fact table. When a cube has multiple fact tables, the measures from each fact table are organized into measure groups, and a measure group is related to a specific set of dimensions by defined dimension relationships. These relationships are defined by specifying the participating tables in the data source view and the granularity of the relationship. Related topic:Dimension Relationships.