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In data warehousing granular data or the data grain in a fact table helps define the level of measurement of the data stored It also determines which dimensions will be included to make up the grain These measurements of fact describe what you have populated in each row.
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Granular data is detailed data or the lowest level that data can be in a target set It refers to the size that data fields are divided into in short how detailoriented a single field is A good example of data granularity is how a name field is subdivided if it is contained in a single field or subdivided into its constituents such as first name middle name and last name.
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The data warehouse and its granular data serve as a basis for the data found in the data marts The granular data in the data warehouse are summarized and otherwise aggregated into the form that each data mart requires Note that each data mart and each organization will have their own way of summarizing and aggregating data.
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How Useful is Your Data? The Importance of Granularity
What is Granular Data? Definition from Techopedia
Data Grain: What’s the Right Level of Granularity When
Data granularity is the level of detail considered in a model or decision making process or represented in an analysis report The greater the granularity the deeper the level of detail Increased granularity can help you drill down on the details of each marketing channel and assess its efficacy efficiency and overall ROI.
