A cube is an Analysis Services object that provides a multidimensional representation of data. When you build a cube in Analysis Services, you define measures and dimensions. Measures are the quantitative values in the database that you want to analyze (e.g., Mean Time Between Failures and Total Costs). Dimensions define exactly what you want to measure (e.g., Location or Equipment Type). Hierarchies define how the dimensions are aggregated.
Measures, dimensions, and hierarchies define a cube. For each intersection of a dimension and measure, a value is calculated. For example, the Mean Time Between Failures for Centrifugal Pumps in FCC Unit during 1999 could equal 152 Days.
Defining Measures for the Cube
Measures are the quantitative values in the database that you want to analyze. For example, In Work History cube, typical measures are total maintenance cost, total cost, event count, asset count, proactive work cost and so on. Measures are analyzed against the different dimension categories of a cube. For example, you may want to analyze total maintenance cost and event count (your measures) for a particular equipment (a dimension) across functional location during two particular years (levels of a time dimension).
Defining Dimensions for the Cube
The dimensions of a cube represent distinct categories for analyzing business data. Categories such as time, geography, or product line breakdowns are typical cube dimensions.
Dimensions are usually organized into hierarchies of information that map to columns in a relational database. Dimension hierarchies are grouped into levels consisting of dimension members. Each level in a dimension can be rolled together to form the values for the subsequent level. For example, in a time dimension, days roll into months, and months roll into quarters. The following hierarchy provides an example how different levels might be arranged within a dimension:
Refinery
Equipment
Year
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