Title : HYBRID METHODOLOGY FOR EFFECTIVE MAINTENANCE OF DATA WAREHOUSE

Type of Material: Thesis
Title: HYBRID METHODOLOGY FOR EFFECTIVE MAINTENANCE OF DATA WAREHOUSE
Researcher: SEELAM SAI SATYANARAYANA REDDY
Guide: H.R.SUDARSHAN REDDY
Department: Department of Engineering and Technology(Computer Science and Engineering)
Publisher: Bharath University, Chennai
Place: Chennai
Year: 2009
Language: English
Subject: Virtual Storage Access Method
Hypercub
Computer Science and Information Technology
Engineering and Technology
Dissertation/Thesis Note: PhD; Department of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai; 2009
Fulltext: Shodhganga

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035__|a(IN-AhILN)th_454482
040__|aBHAU_600073|dIN-AhILN
041__|aeng
100__|aSEELAM SAI SATYANARAYANA REDDY|eResearcher
110__|aDepartment of Engineering and Technology(Computer Science and Engineering)|bBharath University, Chennai|dChennai|ein
245__|aHYBRID METHODOLOGY FOR EFFECTIVE MAINTENANCE OF DATA WAREHOUSE
260__|aChennai|bBharath University, Chennai|c2009
300__|dDVD
502__|bPhD|cDepartment of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai|d2009
518__|oDate of Registration|d2004-12-13
520__|aData Warehousing has been a buzz word in the industry. Researches have been constantly involved in finding new ways of designing and developing Data Warehousing Architectures, algorithms and tools for bringing together some selected data from multiple heterogeneous databases into a single repository. The real work of taking output from the data warehouse depends largely on how it is managed. Although a lot of research is going on to enhance the design and development of Data warehouse, Very little effort has been spent on the maintenance side. Without proper maintenance data warehouse is not going to give the desired output which is expected of it. In this work a comparison of various architectures of Data Warehousing system, based on analyzed on concepts like wrapper, monitor, integrator, metadata, data quantity indicator is considered. A major reason for data warehouse project failures is poor maintenance. Without proper maintenance desired results are nearly impossible to attain from a data warehouse. Un
650__|aComputer Science and Information Technology|2UGC
650__|aEngineering and Technology|2AIU
653__|aVirtual Storage Access Method
653__|aHypercub
700__|aH.R.SUDARSHAN REDDY|eGuide
856__|uhttp://shodhganga.inflibnet.ac.in/handle/10603/170876|yShodhganga
905__|afromsg

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