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More on OLAP Cubes

The OLAP cube provides the multidimensional way to look at the data. The cube is comparable to a table in a relational database.

The specific design of an OLAP cube ensures report optimization. The design of many databases is for online transaction processing and efficiency in data storage, whereas OLAP cube design is for efficiency in data retrieval. In other words, the storage of OLAP cube data is in such a way as to make easy and efficient reporting. A traditional relational database treats all the data in a similar manner. However, OLAP cubes have categories of data called dimensions and measures.

In the figure below; time, product and location represent the dimensions of the cube, while 80 represents the measure. Note: A dimension is a category of data and a measure is a fact or value.

Dimensions

Dimensions are broad groupings of descriptive data about a major aspect of a business, such as dates, markets and products. Each dimension includes different levels of categories.

For example, you OLAP cube could have a time dimension. This time dimension could be further categorized into year, quarter, and month. These levels of categories, (hierarchies) are what provide the ability to drill-up or drill-down on data in an OLAP cube.

Measures

Measures are actual data values that occupy the cells as defined by the dimensions. Measures are typically stored as numerical fields. For example you are a manufacturer of calculators. The question you want answered is how many of ABC model calculators (product dimension) a particular plant (location dimension) produce did during the month of April 2009 (time dimension). Using the Analysis Module, you find out that a plant produced 4500 ABC cell phones in April 2009. The measure on this example is the 4500.