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Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another ...
Some data warehouses may overwrite existing information with cumulative information; updating extracted data is frequently done on a daily, weekly, or monthly basis. Other data warehouses (or even other parts of the same data warehouse) may add new data in a historical form at regular intervals – for example, hourly.
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 ...
Extract, transform, load (ETL) design and development is the design of some of the heavy procedures in the data warehouse and business intelligence system. Kimball et al. suggests four parts to this process, which are further divided into 34 subsystems [3]: Extracting data; Cleaning and conforming data; Delivering data for presentation
A staging area, or landing zone, is an intermediate storage area used for data processing during the extract, transform and load (ETL) process. The data staging area sits between the data source(s) and the data target(s), which are often data warehouses, data marts, or other data repositories.
According to the Inmon school of data warehousing, a dependent data mart is a logical subset or a physical subset (extract) of a larger data warehouse, isolated for one of the following reasons: A need refreshment for a special data model or schema : e.g., to restructure for OLAP .
In computing, data transformation is the process of converting data from one format or structure into another format or structure. It is a fundamental aspect of most data integration [1] and data management tasks such as data wrangling, data warehousing, data integration and application integration.
Data extraction; Data loading; Data mart; Data transformation (computing) Data vault modeling; Data warehouse appliance; Data warehouse automation; Data build tool; Degenerate dimension; Dimension (data warehouse) Dimensional fact model; Dimensional modeling; DIRKS; Document warehouse