What is granularity in data warehousing?
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).
What does granularity mean in SQL?
the level of detail
Granularity is the level of detail at which data are stored in a database. When the same data are represented in multiple databases, the granularity may differ. As an example, consider the following tables: Both tables contain a cost attribute, but the meaning and use of the columns are different.
What are the three major types of metadata in a data warehouse?
Metadata in a data warehouse fall into three major categories:
- Operational Metadata.
- Extraction and Transformation Metadata.
- End-User Metadata.
What is meant by “granularity of data”?
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 detail-oriented 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…
What is granular data?
Granular data, as the name suggests, is data that is in pieces, as small as possible, in order to be more defined and detailed. The advantage of granular data is that it can be molded in any way that the data scientist or analyst requires, just like granules of sand that conform to their container.
What is granularity in SQL database?
Granularity is the level of detail at which data are stored in a database. When the same data are represented in multiple databases, the granularity may differ. As an example, consider the following tables: Both tables contain a cost attribute, but the meaning and use of the columns are different.