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dc.contributor.advisorJohn R. Williams.en_US
dc.contributor.authorReyes, Eumir P. (Eumir Paulo Reyes Morales)en_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2010-10-12T19:01:58Z
dc.date.available2010-10-12T19:01:58Z
dc.date.copyright2010en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/59267
dc.descriptionThesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 73-74).en_US
dc.description.abstractBusiness intelligence is the set of tools, processes, practices and people that are used to take advantage of information to support decision making in the organizations. Cloud computing is a new paradigm for offering computing resources that work on demand, are scalable and are charged by the time they are used. Organizations can save large amounts of money and effort using this approach. This document identifies the main challenges companies encounter while working on business intelligence applications in the cloud, such as security, availability, performance, integration, regulatory issues, and constraints on network bandwidth. All these challenges are addressed with a systems thinking approach, and several solutions are offered that can be applied according to the organization's needs. An evaluations of the main vendors of cloud computing technology is presented, so that business intelligence developers identify the available tools and companies they can depend on to migrate or build applications in the cloud. It is demonstrated how business intelligence applications can increase their availability with a cloud computing approach, by decreasing the mean time to recovery (handled by the cloud service provider) and increasing the mean time to failure (achieved by the introduction of more redundancy on the hardware). Innovative mechanisms are discussed in order to improve cloud applications, such as private, public and hybrid clouds, column-oriented databases, in-memory databases and the Data Warehouse 2.0 architecture. Finally, it is shown how the project management for a business intelligence application can be facilitated with a cloud computing approach. Design structure matrices are dramatically simplified by avoiding unnecessary iterations while sizing, validating, and testing hardware and software resources.en_US
dc.description.statementofresponsibilityby Eumir P. Reyes.en_US
dc.format.extent74 p.en_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.titleA systems thinking approach to business intelligence solutions based on cloud computingen_US
dc.typeThesisen_US
dc.description.degreeS.M.in System Design and Managementen_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc667715636en_US


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