Data Warehousing: Granularity (Definitions)

"The degree of specificity of information contained in a data element. A fact table that has fine granularity contains many discrete facts, such as individual sales transactions. A table that has coarse granularity stores facts that are summaries of individual elements, such as sales totals per day." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"The level of detail captured in the data warehouse." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"Granularity level is the level of detail of the data in a data warehouse or data mart." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A classification of data based upon the level of detail at which data is recorded. Atomic, base, and summary are all classifications of data granularity." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"The level of detail contained in a unit of data. The more detail there is, the lower the level of granularity. The less detail there is, the higher the level of granularity." (William H Inmon, "Building the Data Warehouse", 2005)

"Refers to the level of detail represented by the values stored in a table’s row. Data stored at their lowest level of granularity are said to be atomic data." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed, 2011)

"Granularity refers to the smallest reusable element of information. See also physical granularity." (Charles Cooper & Ann Rockley, "Managing Enterprise Content: A Unified Content Strategy, 2nd Ed.", 2012)

"A term sometimes used to describe the level of detail used in obtaining information." (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"The level of detail found in a record of data" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"Granularity refers to the level of detail or precision for a specific information resource property. For instance, the postal address of a particular location might be represented as several different data items, including the number, street name, city, state, country and postal code (a high-granularity model). It might also be represented in one single line including all of the information above (a low-granularity model)." (Robert J Glushko, "The Discipline of Organizing: Professional Edition" 4th Ed, 2016)