DISTRIBUTED DATA WAREHOUSE SYSTEMS   Term Paper ID:31845 Click to get this paper

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Paper Abstract: Considers key factors regarding data warehousing. Goal of data warehousing. Differences of data warehousing and relational databases. Paper Introduction: Distributed Data Warehouse Systems Introduction Data warehousing is particularly popular in environments which havecomplex data requirements and a broad spectrum of data types contained inits database The goal of data warehousing is to take full advantage ofthe power of hardware to contain large quantities of data and use thedatabases to manipulate that data Although not yet implemented across allcomputing environments data warehousing is becoming popular as hardwarebecomes more powerful and cost effective Analysis Relational databases which dominated database management systemsuntil the late Text of the Paper: The entire text of the paper is shown below. However, the text is somewhat scrambled. We want to give you as much information as we possibly can about our papers and essays, but we cannot give them away for free. In the text below you will find that while disordered, many of the phrases are essentially intact. From this text you will be able to get a solid sense of the writing style, the concepts addressed, and the sources used in the research paper. Instead, a number of organizations have decided to use datamarts, which are smaller and more focused than data warehouses. Opennness and concurrency is critical to thesuccess of a data warehouse. Tools for managing meta data need to bedeveloped as do administrative tools which address meta data issues(Worsley 14). In orderto realize these benefits, however, careful security processes must be putinto place so that users have a high level of confidence in the integrityof the data (Trunick 6 ). Through a combination of meta data analysisand modeling, users are better able to understand how each of their systemsfits into the larger ERP system. Analysis Relational databases, which dominated database management systemsuntil the late 199 s, were challenged by object-oriented databases(Kentouris ITEM 41 4 B). Regardlessof whether a data mart or data warehouse is used, companies are advisedthat they should not expect dollar savings; instead, they will seeincreased productivity through better management of their data. The research and developmentwhich has supported the creation of data warehouses and data marts has beenlargely driven by the market: as customers have demanded greater access tovast stores of information kept on large servers, software vendors haveresponded with various data warehouses and data marts. Works CitedKentouris, Chris. "Weapons of Mass Confusion." Transportation & Distribution 44(Feb 2 3): 59-61.Worsley, Chris. Because of the vast amounts of data stored in data warehouses,it is critical that meta data be accurate and synchronized to the changeswhich occur in the data. In this way, those types of informationwhich were difficult to organize into relational databases--such asgraphics, sounds and pictures--can be put into databases and easilyaccessed by users in either distributed or nondistributed environments. As a result, therecan be considerable differences in the data warehousing capabilities ofvarious products depending on the market support of their manufacturer, andlittle homogeneity (Trunick 61). Object-oriented databases enable users to accessvastly different types of data and do so in a way which is efficient andwhich increases productivity. This is what led to the term "data warehouse." Various methods have been developed for retrieving information from thedata warehouse; commonly referred to collectively as data mining, thesetechniques give companies the ability to use data in ways which werepreviously unavailable because of the sheer size of the data involved.Today's data warehouses are scalable and transparent to users (Worsley 13). By bringing together all of the components of a company'svarious computer systems, including those relating to customers, employees,vendors, products, inventory, and financials, companies are able to createlarge repositories of data. "Making the Most Out of Warehousing." Securities Industry News (Apr 12, 2 4): ITEM 41 4 B.Trunick, Perry A. Throughout the development of data warehouses, academics have beencritical of the concept and its application. The goal of data warehousing is to take full advantage ofthe power of hardware to contain large quantities of data and use thedatabases to manipulate that data. Conclusion Data warehousing offers an attractive way for companies to mange thevast amounts of information that is generated as business is transacted.Meta data management makes it possible to warehouse data that is difficultto retrieve from traditional databases, and data mining techniques makes itpossible for companies to use data in ways that were previously unavailableand even unimaginable. Although not yet implemented across allcomputing environments, data warehousing is becoming popular as hardwarebecomes more powerful and cost effective. Although a number of large companies have implemented data warehouses,the size of the data stored in such warehouses and the costs associatedwith developing these projects has prevented some companies from takingthis route. Despite this, data warehouses are dependent on thetools that support the data management, and failure to implement effectivetools-including security processes-can result in compromised data that doesnot meet the needs of the organization. Data warehouses address the weaknesses in relational databases byoffering historical data, integrating data and offering detailed as well assummary data. Distributed Data Warehouse Systems Introduction Data warehousing is particularly popular in environments which havecomplex data requirements and a broad spectrum of data types contained inits database. Ashardware becomes more accommodating--in the sense of being more powerfuland less expensive--these types of databases are likely to gain inpopularity over traditional relational databases. "Data Warehousing in 'Real Time.'" Software World, 34(Sep 2 3): 13-14. Meta data is the summary information about what data is in thewarehouse. 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