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dc.contributor.advisorStuart Madnick.en_US
dc.contributor.authorPullokkaran, Laijo Johnen_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2014-10-08T15:23:49Z
dc.date.available2014-10-08T15:23:49Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/90703
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2013.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 59).en_US
dc.description.abstractBusiness Intelligence is an essential tool used by enterprises for strategic, tactical and operational decision making. Business Intelligence most often needs to correlate data from disparate data sources to derive insights. Unifying data from disparate data sources and providing a unifying view of data is generally known as data integration. Traditionally enterprises employed ETL and data warehouses for data integration. However in last few years a technology known as "Data Virtualization" has found some acceptance as an alternative data integration solution. "Data Virtualization" is a federated database termed as composite database by McLeod/Heimbigner's in 1985. Till few years back Data Virtualization weren't considered as an alternative for ETL but was rather thought of as a technology for niche integration challenges. In this paper we hypothesize that for many BI applications "data virtualization" is a better cost effective data integration strategy. We analyze the system architecture of "Data warehouse" and "Data Virtualization" solutions. We further employ System Dynamics Model to compare few key metrics like "Time to Market" and "Cost of "Data warehouse" and "Data Virtualization" solutions. We also look at the impact of "Enterprise Data Standardization" on data integration.en_US
dc.description.statementofresponsibilityby Laijo John Pullokkaran.en_US
dc.format.extent59 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectSystem Design and Management Program.en_US
dc.titleAnalysis of data virtualization & enterprise data standardization in business intelligenceen_US
dc.title.alternativeAnalysis of data virtualization and enterprise data standardization in business intelligenceen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc890947872en_US


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