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When we design data marts, we need to be aware that Analysis Services does not treat all data types the same way. The cube will be much faster, for both processing and querying, if we use the right data type for each column. Here we provide a brief table that helps us during the design of the data mart, to choose the best data type for each column type:
Clearly, we should always try to use the smallest data type that will be able to hold any single value within the whole range of values needed by the application.
NOTICE
This is the rule for relational tables. However, you also need to remember that the equivalent measure data type in Analysis Services must be large enough to hold the largest aggregated value of a given measure, not just the largest value present in a single fact table row.
Always remember that there are situations in which the rules must be overridden.If we have a fact table containing 20 billion rows, each composed of 20 bytes and a column that references a date, then it might be better to use a SMALLINT column for the date, if we find a suitable representation that holds all necessary values. We will gain 2 bytes for each row, and that means a 10% in the size of the whole table.