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Granularity means the level of detail of your data within the data structure. In a typical Data Warehouse one might find very detailed data (such as seconds, single product, one specific attribute) and aggregated data (such as total number of, monthly orders, all products).

The higher the granularity of a fact table the more data (or in an excel sheet: rows) you will have. But the granularity of your data also determines what kind of information you can get out of the stored data. So to aggregate data you need of course the same granularity. (A weekly report can only be generated when you have time realted data stored. At least it should be a “week”, better it is to have “day”.)

<note tip>Example: You can slice an hour down in different granularity. A very rough/ low granularity would be the 1 hour itself (1 data). But one can also say 60 minutes. (60 data: 1st minute, 2nd minutes, etc.) The finer or higher your granularity goes the more data you will have to store. So an hour can also be 3600 seconds or even 3600000 milliseconds.</note>

Important for managers to understand, because:

  • your granularity will determine your storage space. The higher/ finer your granularity is, the more date you have to store.
  • your granularity will determine what kind of information (reports, etc.) you can create/ get out of your information system.

Alexander Salatzkat

glossary/g/granularity.txt · Last modified: 2020/08/20 13:27 (external edit)