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dc.creatorAnagnostopoulos I., Zeadally S., Exposito E.en
dc.date.accessioned2023-01-31T07:31:19Z
dc.date.available2023-01-31T07:31:19Z
dc.date.issued2016
dc.identifier10.1007/s11227-016-1677-z
dc.identifier.issn09208542
dc.identifier.urihttp://hdl.handle.net/11615/70519
dc.description.abstractToday, an enormous amount of data is being continuously generated in all walks of life by all kinds of devices and systems every day. A significant portion of such data is being captured, stored, aggregated and analyzed in a systematic way without losing its “4V” (i.e., volume, velocity, variety, and veracity) characteristics. We review major drivers of big data today as well the recent trends and established platforms that offer valuable perspectives on the information stored in large and heterogeneous data sets. Then, we present a classification of some of the most important challenges when handling big data. Based on this classification, we recommend solutions that could address the identified challenges, and in addition we highlight cross-disciplinary research directions that need further investigation in the future. © 2016, Springer Science+Business Media New York.en
dc.language.isoenen
dc.sourceJournal of Supercomputingen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84962978213&doi=10.1007%2fs11227-016-1677-z&partnerID=40&md5=8682987ad680446ca3cd50d4e99837b7
dc.subjectData handlingen
dc.subjectData privacyen
dc.subjectCross-disciplinary researchen
dc.subjectData analyticsen
dc.subjectData cleansingen
dc.subjectData curationen
dc.subjectDevices and systemsen
dc.subjectHeterogeneous dataen
dc.subjectResearch challengesen
dc.subjectTrusten
dc.subjectBig dataen
dc.subjectSpringer New York LLCen
dc.titleHandling big data: research challenges and future directionsen
dc.typejournalArticleen


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