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dc.contributor.advisorSinan K. Aral.en_US
dc.contributor.authorShukla, Soumyaen_US
dc.contributor.otherSloan School of Management.en_US
dc.date.accessioned2016-09-30T19:33:16Z
dc.date.available2016-09-30T19:33:16Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/104515
dc.descriptionThesis: S.M. in Management Studies, Massachusetts Institute of Technology, Sloan School of Management, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages [85]-[90]).en_US
dc.description.abstractIn today's age of 'Information Explosion' most companies are struggling with optimally utilizing all the data generated. The last two decades have seen tremendous progress in data collection, storage, processing and visualization technologies. The last decade has seen a remarkable growth in the types of user data: social, web and more recently mobile. As newer sources of data emerge, our ability to separate an individual from a segment improves. The data being analyzed is not just structured in nature. Several processing technologies are analyzing unstructured data for insights. Emerging technologies based on machine learning are improving our ability to migrate decision making from discovery & diagnostics to prediction & preemption. The rise of Internet of Things enhances the opportunity to collect further granular data. At the same time, as system efficiency increases, concerns about privacy loss and malpractices also increase. The world of big data is more complex and controversial than ever before. This study focuses on creating a baseline of big data technologies and attempts to identify near term trends within the horizon of 5 years due to the pace of technological development. The study places special emphasis on E-commerce Sales & Marketing analytics to determine current challenges and develops a key considerations framework for a new entrant in that space.en_US
dc.description.statementofresponsibilityby Soumya Shukla.en_US
dc.format.extent101 unnumbered 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.subjectSloan School of Management.en_US
dc.titleStudy of big data analytics landscape : considerations for market entry of an E-commerce analytics vendoren_US
dc.title.alternativeConsiderations for market entry of an E-commerce analytics vendoren_US
dc.typeThesisen_US
dc.description.degreeS.M. in Management Studiesen_US
dc.contributor.departmentSloan School of Management
dc.identifier.oclc958296268en_US


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