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In decision support and analytics, data can be analyzed and displayed at different granularities. Granularity refers to the amount of aggregation and the amount of detail in the data. Highly aggregated or summarized data is low granularity; highly detailed data is high granularity. The greater/higher the granularity, the greater/higher the amount of detail and the deeper the level of detail.

Granularity of data refers to the detail with which data fields are sub-divided. For example, a postal address can be stored with low granularity as a single field or with high granularity as multiple atomic fields.

Granularity for a data analysis refers to the detail of the data in the analysis. For example, retail sales data can be analyzed for a group of stores and that analysis or dashboard has low granularity or an analysis with high granularity would analyze individual stores and present decision support results at the store level.

Related Terms: drill down

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