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Topic: Data warehouse

Related Topics

Extract, transform, load

Data mining

Data warehousing

Data mart

Document warehouse

Business intelligence

Database management system

OLAP

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OLTP

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	MySQL AB :: Data Warehouse & Berichtswesen
		Während noch vor wenigen Jahren die meisten Daten in zentralen Data-Warehouse- und wenigen abteilungsinternen Datamart-Systemen gespeichert wurden, registrieren wir heute den Einsatz kleinerer verteilter Datendepots überall in Unternehmen.
		Jetzt Webseminar "MySQL for Data Warehouse" abrufen »
		Und da MySQL sich durch seine hohe Benutzerfreundlichkeit auszeichnet, können sie dies mit nur wenigen oder gar keinen Data-Warehouse-Spezialisten und Datenbankadministratoren bewerkstelligen.
	www.mysql.de /why-mysql/application-scenarios/data-warehouse.html (0 words)

	Data Warehousing Technology
		Universal data access means that, theoretically at least, end-users, regardless of location or Information Access tool, should be able to access any or all of the data in the enterprise that is necessary for them to do their job.
		Data Staging is also called copy management or replication management, but in fact, it includes all of the processes necessary to select, edit, summarize, combine and load data warehouse and information access data from operational and/or external databases.
		The scope of a data warehouse may be as broad as all the informational data for the entire enterprise from the beginning of time, or it may be as narrow as a personal data warehouse for a single manager for a single year.
	www.kenorrinst.com /dwpaper.html (3513 words)

	Data Warehouse Glossary - IT@CSUMB.EDU
		Data mining: Discovery mode of data analysis, or analyzing detail data to unearth unsuspected or unknown relationships, patterns and associations that might be of value to the organization.
		Data ownership: Responsibility for determining the required quality of the data, for establishing security and privacy for the data and determining the availability and performance requirements for the data.
		Data Warehouse: A collection of integrated, subject-oriented databases designed to support the DSS function, where each unit of data is relevant to some moment in time.
	it.csumb.edu /departments/data/glossary.html (6650 words)

	Data Warehouse Description
		Source data analysis and the efficient and accurate movement of source data into the warehouse environment are critical to the success of a data warehouse project.
		Data in a data warehouse should be reasonably current, but not necessarily up to the minute, although developments in the data warehouse industry have made frequent and incremental data dumps more feasible.
		In data warehouse environments specifically, there needs to be a means to ensure the integrity of data first by having procedures to control the movement of data to the warehouse from operational systems and second by having controls to protect warehouse data from unauthorized changes.
	www.mnhs.org /preserve/records/dwintro.html (847 words)

	The Data Warehousing Information Center - A Definition of Data Warehousing
		Ralph states that a data warehouse is "a copy of transaction data specifically structured for query and analysis".
		Queries and reports generated from data stored in a data warehouse may or may not be used for analysis.
		Data warehousing is not necessarily for the needs of "decision makers" or used in the process of decision making.
	www.dwinfocenter.org /defined.html (429 words)

	Data Warehouse = DataHabitat
		Data warehousing is a proven technology, up to now only available to Fortune 1000 companies, because of high software and implementation costs.
		Data Warehousing is, therefore, the process of creating an optimized database environment that will concentrate all or part of your company’s data - despite its platform, source application, or data source — for the purposes of business intelligence.
		Essentially, a data warehouse is a copy of the operational data created by one or many applications which has been optimized for reporting and analysis.
	www.datahabitat.com /datawarehouse.html (842 words)

	DBAzine.com: Constructing a Data Warehouse
		To understand how a warehouse can benefit you and what is required to manage a warehouse, you must first understand how a data warehouse is constructed and established.
		Data in a warehouse needs to be accurate and of high quality if business decisions will be made using it.
		Therefore, if someone is interested in having data that is current within minutes or seconds, some method should be devised to allow users who need real-time updates to the warehouse to bear the cost of the hardware and software required to provide that level of data currency.
	www.dbazine.com /datawarehouse/dw-articles/moulder1 (2138 words)

	The Federated Data Warehouse
		When data mart design is dictated by the data that exists in operational systems, the common business model is used, and updated as appropriate, in parallel with the development of underlying data mart data models.
		Data profiling and warehouse design tools can be used in a series of iterative steps to develop the design of the staging area and to identify the rules for mapping, cleansing and transforming the source data into the format required by the staging area.
		Using data profiling and data reengineering tools ahead of ETL tool processing reduces the likelihood of data quality problems occurring in the data warehouse, and can dramatically improve project success rates and the return on investment of data warehousing projects.
	dmreview.com /master.cfm?NavID=198&EdID=1953 (1267 words)

	Data Warehouse
		The University's Data Warehouse is divided into the following data collections: BRS (Student Billing and Receivables), General Ledger, Position Inventory, Salary Management, Space@Penn, Sponsored Projects, and Student Data.
		Data collection information includes the collection's refresh schedule, data diagrams, table and data element documentation, data training, and data security.
		This includes basic information about data base queries, historical information about Penn's data warehouse, the access request forms you must submit for authorization to use the Warehouse, query tools used at Penn to retrieve data, training, support services available for help, general information about Warehouse security, and updates to the warehouse.
	www.upenn.edu /computing/da/dw (201 words)

	How’s Your Data Warehouse TCO?
		Data volumes are being driven by the need for more frequent updates, new data sources and longer data retention requirements.
		A revealing data point from the 2005 IT Toolbox Data Warehouse survey is that more than 45% of the respondents expect their data warehouse size to increase at least 49%.
		Data warehouse appliances provide a new solution for IT organizations that need to contain or reduce the costs of their data warehouse infrastructure.
	www.datallegro.com /news/data_warehouse_tco.asp (1177 words)

	Database Pipeline \| The Data Quality Audit
		Data quality problems are often widespread and originate in your source systems, their applications, and operational processes.
		Guidelines for sourcing data into the warehouse must be established in order to avoid simply sourcing data because it is part of an existing record.
		With the source data applications providing an unfettered environment for end users, coupled with incomplete transformation, cleansing, and warehouse maintenance processes, the warehouse data is guaranteed to be less than satisfactory.
	www.databasepipeline.com /22104353 (787 words)

	Data warehouse appliance success stories from Ahold, Amazon.com, Epsilon and others
		They are using Netezza's data warehouse appliance to understand advertising effectiveness and to spin up "teramarts" (or very large marts) on demand for quick, deep analysis of web behavior.
		Today, with the Netezza data warehouse appliance, the company can do the same analysis in a few hours with much more data, and is realizing significant benefits as a result.
		With the NPS system, Catalina has a scalable data warehouse architecture that can now accommodate 70 times more queries on 5 times the data and a greater number of users than with its previous system, giving its retail customers faster and more comprehensive access to their data.
	www.netezza.com /customers/results.cfm (814 words)

	UNM Data Warehouse Home
		Data from the prior Spring semester in the Current tables are rolled into Historical tables when registration begins for the current Spring semester.
		The Prospective Student Data Mart is made up of tables that contain information about prospective students, their informational interests, the type of contact that they made with the UNM and UNM's responses to their interests.
		The purpose of the University of New Mexico's (UNM) Data Warehouse is to provide a common database containing pertinent student, financial, and employee data for operational and administrative reporting, as well as executive decision support.
	its.unm.edu /dwhpage/DWHHome.htm (1829 words)

	Enterprise Data Warehouse - Teradata
		The Teradata Warehouse solution allows you to analyze business operations and drive better, faster decisions by providing a complete view of your business and giving you the flexibility and agility to compete.
		Teradata Warehouse provides integrated, optimized and extensible technology and services for a single application-neutral repository of your current and historical data, forming the framework of the business intelligence architecture.
		Active Data Warehousing, the foundation of Active Enterprise Intelligence, drives vital data into the hands of your front-line decision makers, extending traditional data warehouse functionality into the realm of tactical decision making through near real-time information access and analyses and predictive analytics.
	www.teradata.com /enterprise-data-warehouse (495 words)

	Data Warehouse
		Making this data available to a wide audience of business users is one of the most significant challenges for today's businesses.In response, Persys, Inc. has chosen Microsoft SQL Server Data Warehousing Framework to build data warehouses and data marts.
		Data marts contain a subset of corporate-wide data that is built for use by an individual department or division of an organization.
		Unlike the enterprise warehouse, data marts are often built from the bottom up by departmental resources for a specific decision support application or group of users.
	www.persysinc.com /persys_database_datawarehouse.aspx (335 words)

	Data Warehouse Quality Management
		Data warehouses also need to evolve over time, so they are incrementally built.
		In data warehousing, the general number of access to the data warehouse would be a metric.
		To illustrate, he describes a “typical” data warehousing curve: When the warehouse is first implemented, after a week or so the usage level is very high because news about the warehouse has spread and users are exploring.
	www.users.qwest.net /~lauramh/resume/dwqual.htm (2366 words)

	Developing a Data Warehouse Architecture
		A data warehouse architecture is a description of the elements and services of the warehouse, with details showing how the components will fit together and how the system will grow over time.
		Like the house analogy, the warehouse architecture is a set of documents, plans, models, drawings, and specifications, with separate sections for each key component area and enough detail to allow their implementation by skilled professionals.
		But where dimensions intersect in the data model the definitions have to be the same—the same customer who buys is the same that builds.
	www.users.qwest.net /~lauramh/resume/thorn.htm (2008 words)

	Data Warehouse Process
		Data Warehouses are designed around the major subject areas of the enterprise; the operational environment is designed around applications and functions.
		Data Warehouses do not contain information that will not be used for informational or analytical processing; operational databases contain detailed data that is needed to satisfy processing requirements but which has no relevance to management or analysis.
		The Data Warehouse project team is expanded to include the members needed to construct and deploy the Warehouse, and a detailed work plan for the design and implementation of the iteration project is developed and presented to the customer organization for approval.
	www.gantthead.com /process/processMain.cfm?ID=2-2357-2 (4049 words)

	data warehouse - a definition from Whatis.com
		A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect.
		Data from various online transaction processing (OLTP) applications and other sources is selectively extracted and organized on the data warehouse database for use by analytical applications and user queries.
		Data warehousing emphasizes the capture of data from diverse sources for useful analysis and access, but does not generally start from the point-of-view of the end user or knowledge worker who may need access to specialized, sometimes local databases.
	whatis.techtarget.com /definition/0,289893,sid9_gci211904,00.html (211 words)

	Amazon.com: Data Warehouse Method, The: Books: Tom Debevoise (Site not responding. Last check: )
		A quality data warehouse serves the strategic intent of the organization, is created with the best available data, and is achieved at an optimal rate.
		Within the object oriented data warehouse methods that are presented here, techniques are developed that separate and assign responsibilities of the evaluations of an organization's data among the multiple tiers of the organization's environment.
		For the large data warehouse to run most efficiently, all of the components should be tightly integrated with a management module.
	www.amazon.com /Data-Warehouse-Method-Tom-Debevoise/dp/0130813060 (5047 words)

	Data Warehouse Project Management
		Intimate knowledge of the data and its relationships is the distinction between a generic project manager and data warehouse project manager.
		As a competent project manager with no data warehousing experience, it is still possible to deliver a data warehouse as planned, but this requires strong reliance on the project team for subject matter expertise.
		The data warehouse becomes the heartbeat of the business, where decisions are made from the data intelligence it provides.
	www.dmreview.com /article_sub.cfm?articleId=1048521 (1651 words)

	RTTS: Services - Data Warehouse Testing
		RTTS’ Data warehouse testing strategy focuses on the two main structures within a data warehouse architecture: the ETL (Extraction, Transformation and Loading) layer and the data warehouse with its front-end applications.
		To successfully deploy a data warehouse, an organization must be confident that the reports generated display the proper data.
		The focus of this whitepaper is to explain how to ensure that the data in the data warehouse is properly loaded from the source system(s).
	www.rttsweb.com /platforms/datawarehouse (462 words)

	Rensselaer Data Warehouse Project
		The fundamental goal of the Rensselaer Data Warehouse Project is to integrate administrative data into a consistent information resource that supports planning, forecasting, and decision-making processes at Rensselaer.
		To achieve this goal, the Data Warehouse Group within the Integrated Administrative Computing Services (IACS) department is serving as the primary implementation team, working with implementation groups that are composed of members of the Rensselaer community.
		The fundamental goals of this effort were to identify data warehouse requirements, facilitate the prioritization of warehouse deliverables, and determine success criteria for the Rensselaer Data Warehouse Project, thus ensuring that we are properly focused before expending resources and making significant investments.
	www.rpi.edu /datawarehouse (326 words)

	Data Warehouse Design, Development, and Implementation
		Managing the design, development, implementation, and operation of even a single corporate data warehouse can be a difficult and time consuming task.
		Developing a data warehouse from scratch, as strange as it sounds, is by far the easiest.
		Information and Data modeling, along with the definition of the metadata, is the single most important activity in the design of a data warehouse.
	www.horsburgh.com /h_dataw.html (2250 words)

	What is data warehouse? - a definition from Whatis.com
		Typically, a data warehouse is housed on an enterprise mainframe server.
		Data from various online transaction processing (OLTP) applications and other sources is selectively extracted and organized on the data warehouse database for use by analytical applications and user queries.
		Data warehousing emphasizes the capture of data from diverse sources for useful analysis and access, but does not generally start from the point-of-view of the end user or knowledge worker who may need access to specialized, sometimes local databases.
	searchsqlserver.techtarget.com /sDefinition/0,,sid87_gci211904,00.html (302 words)

	Data Warehouse Training / Learn Data Warehousing and Data Mining (Site not responding. Last check: )
		Nearly every Fortune 500 corporation is either planning to build a data warehouse or is currently in the process of building one.
		However, many data warehouse projects fail because building a data warehouse is a difficult task that requires a combination of business sponsorship and solid database systems expertise.
		Once a warehouse is built, data mining techniques are frequently employed to identify trends in the warehouse that may not be readily apparent.
	www.carriglearning.com /courses/cd_cetdbadwm.shtml (556 words)

	Oracle FAQ: Data Warehousing (Site not responding. Last check: )
		ETL is the Data Warehouse acquisition processes of Extracting, Transforming (or Transporting) and Loading (ETL) data from source systems into the data warehouse.
		Data in a multi-dimensional database is stored as business people views it, allowing them to slice and dice the data to answer business questions.
		Data is automatically directed to the correct partition based on data ranges or hash values.
	www.orafaq.com /faqwh.htm (1052 words)

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