datawarehousing - определение. Что такое datawarehousing
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Что (кто) такое datawarehousing - определение

SYSTEM USED FOR REPORTING AND DATA ANALYSIS, AS A CORE COMPONENT OF BUSINESS INTELLIGENCE
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  • Data warehouse overview
  • The basic architecture of a data warehouse
  • ELT]]-based data warehouse architecture
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data warehouse         
<database> (Or corporate data warehouse, CDW) Any system for storing, retrieving and managing large amounts of data. Data warehouse software often includes sophisticated compression and hashing techniques for fast searches, as well as advanced filtering. A data warehouse is often a {relational database} containing a recent snapshot of corporate data and optimised for searching. Planners and researchers can use this database without worrying about slowing down day-to-day operations of the production database. The latter can be optimised for transaction processing (inserts and updates). Compare data mart. (2007-05-16)
Data warehouse         
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.
data warehousing         

Википедия

Data warehouse

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. Data warehouses 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. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.

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 data warehouse for reporting.

Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system.