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Data Warehouse/Business Intelligence

A Data Warehouse is a repository of an organization's electronically stored data. Data warehouses are designed to facilitate reporting and analysis.
Data warehouse focuses on data storage. However, the means to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata. Data warehouses are optimized for speed of data analysis.
Architecture, in the context of an organization's data warehousing efforts, is a conceptualization of how the data warehouse is built. There is no right or wrong architecture, but rather there are multiple architectures that exist to support various environments and situations. The worthiness of the architecture can be judged from how the conceptualization aids in the building, maintenance, and usage of the data warehouse.
One possible simple conceptualization of a data warehouse architecture consists of the following interconnected layers:
Operational Database Layer:  The source data for the data warehouse — An organization's Enterprise Resource Planning systems fall into this layer.
Data access layer:  The interface between the operational and informational access layer — Tools to extract, transform, load data into the warehouse fall into this layer.
Metadata Layer: The data directory - This is usually more detailed than an operational system data directory. There are dictionaries for the entire warehouse and sometimes dictionaries for the data that can be accessed by a particular reporting and analysis tool.
Informational access layer The data accessed for reporting and analyzing and the tools for reporting and analyzing data — Business intelligence tools fall into this layer.
 
Business Intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. Business intelligence applications can be:
  1. Mission-critical and integral to an enterprise's operations or occasional to meet a special requirement
  2. Enterprise-wide or local to one division, department, or project
  3. Centrally initiated or driven by user demand
Business Intelligence often aims to support better business decision-making. Thus a BI system can be called a decision support system (DSS). Though the term business intelligence is often used as a synonym for competitive intelligence, because they both support decision making, BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence, is done by gathering, analyzing and disseminating information with or without support from technology and applications, and focuses on all-source information and data (unstructured or structured), mostly external to, but also internal to a company, to support decision making. Often BI applications use data gathered from a data warehouse or a data mart. However, not all data warehouses are used for business intelligence nor do all business intelligence applications require a data warehouse.
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A data warehouse is a repository of an organization's electronically stored data. Data warehouses are designed to facilitate reporting and analysis
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