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Measure (data Warehouse)
In a data warehouse, a measure is a property on which calculations (e.g., sum, count, average, minimum, maximum) can be made. Example For example, if a retail store sold a specific product, the quantity and prices of each item sold could be added or averaged to find the total number of items sold or the total or average price of the goods sold. Use of ISO representation terms When entering data into a metadata registry such as ISO/IEC 11179, representation terms such as number, value and measure are typically used as measures. See also * Data warehouse * Dimension (data warehouse) A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Commonly used dimensions are people, products, place and time. (Note: People and time sometimes are not modeled as dimensions.) ... References * Kimball, Ralph et al. (1998); ''The Data Warehouse Lifecycle Toolkit'', p17. Pub. Wiley. . * Kimball, Ralph (1996); ''The Data Warehouse ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for Business reporting, reporting and data analysis and is considered a core component of business intelligence. DWs are central Repository (version control), repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. The data stored in the warehouse is uploaded from the operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the DW for reporting. Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system. ETL-based data warehousing The typical extract, transform, load (ETL)-based data warehouse uses ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ISO/IEC 11179
The ISO/IEC 11179 Metadata Registry (MDR) standard is an international ISO/IEC standard for representing metadata for an organization in a metadata registry. It documents the standardization and registration of metadata to make data understandable and shareable. Intended purpose Organizations exchange data between computer systems precisely using enterprise application integration technologies. Completed transactions are often transferred to separate data warehouse and business rules systems with structures designed to support data for analysis. A de facto standard model for data integration platforms is the Common Warehouse Metamodel (CWM). Data integration is often also solved as a problem of data, rather than metadata, with the use of so-called master data. ISO/IEC 11179 claims that it is a standard for metadata-driven exchange of data in an heterogeneous environment, based on exact definitions of data. Structure of an ISO/IEC 11179 metadata registry The ISO/IEC 11179 mod ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Representation Term
A representation term is a word, or a combination of words, that semantically represent the data type (value domain) of a data element. A representation term is commonly referred to as a ''class word'' by those familiar with data dictionaries. ISO/IEC 11179-5:2005 defines ''representation term'' as a ''designation of an instance of a representation class'' As used in ISO/IEC 11179, the representation term is that part of a data element name that provides a semantic pointer to the underlying data type. A ''Representation class'' is a class of representations. This ''representation class'' provides a way to classify or group data elements. A ''Representation Term'' may be thought of as an attribute of a data element in a metadata registry that classifies the data element according to the type of data stored in the data element. Representation terms are typically "approved" by the organization or standards body using them. For example, the UN publishes its approved list as part o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for Business reporting, reporting and data analysis and is considered a core component of business intelligence. DWs are central Repository (version control), repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. The data stored in the warehouse is uploaded from the operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the DW for reporting. Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system. ETL-based data warehousing The typical extract, transform, load (ETL)-based data warehouse uses ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dimension (data Warehouse)
A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Commonly used dimensions are people, products, place and time. (Note: People and time sometimes are not modeled as dimensions.) In a data warehouse, dimensions provide structured labeling information to otherwise unordered numeric measures. 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. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics. Typically dimensions in a data warehouse are organiz ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ralph Kimball
Ralph Kimball (born July 18, 1944) is an author on the subject of data warehousing and business intelligence. He is one of the original architects of data warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast. His bottom-up methodology, also known as dimensional modeling or the Kimball methodology, is one of the two main data warehousing methodologies alongside Bill Inmon. He is the principal author of the best-selling books ''The Data Warehouse Toolkit'', ''The Data Warehouse Lifecycle Toolkit'', ''The Data Warehouse ETL Toolkit'' and ''The Kimball Group Reader'', published by Wiley and Sons. Career After receiving a Ph.D. in 1973 from Stanford University in electrical engineering (specializing in man-machine systems), Ralph joined the Xerox Palo Alto Research Center (PARC). At PARC Ralph was a principal designer of the Xerox Star Workstation, the first commercial product to use mice, icons and windows. Kimball the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Warehousing
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 considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. The data stored in the warehouse is uploaded from the operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the DW for reporting. Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system. ETL-based data warehousing The typical extract, transform, load (ETL)-based data warehouse uses staging, data integration, and access layers to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
