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The dimension is a data set composed of individual, non-overlapping data elements. The primary functions of dimensions are threefold: to provide filtering, grouping and labelling. These functions are often described as "slice and dice". A common data warehouse example involves sales as the measure, with customer and product as dimensions.
Example of a basic architecture of a data warehouse. An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the ...
CWM models enable users to trace the lineage of data – CWM provides objects that describe where the data came from and when and how the data was created. Instances of the metamodel are exchanged via XML Metadata Interchange (XMI) documents. Initially, CWM contained a local definition for a data translation facility.
In data management and data warehousing, a slowly changing dimension (SCD) is a dimension that stores data which, while generally stable, may change over time, often in an unpredictable manner. [1] This contrasts with a rapidly changing dimension , such as transactional parameters like customer ID, product ID, quantity, and price, which undergo ...
Data vault is designed to avoid or minimize the impact of those issues, by moving them to areas of the data warehouse that are outside the historical storage area (cleansing is done in the data marts) and by separating the structural items (business keys and the associations between the business keys) from the descriptive attributes.
Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...
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Azure SQL Database is built on the foundation of the SQL server database and therefore, kept in sync with the latest version [2] of it by using the common code base. Since the cloud version of the database technology strives to decouple it from the underlying computing infrastructure, it doesn't support some of the context specific T-SQL ...