Towards interactive data exploration

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buir.contributor.authorBasık, Fuat
buir.contributor.authorUsta, Arif
dc.citation.epage190en_US
dc.citation.spage177en_US
dc.citation.volumeNumber337en_US
dc.contributor.authorBinnig, C.en_US
dc.contributor.authorBasık, Fuaten_US
dc.contributor.authorBuratti, B.en_US
dc.contributor.authorÇetintemel, U.en_US
dc.contributor.authorChung, Y.en_US
dc.contributor.authorCrotty, A.en_US
dc.contributor.authorCousins, C.en_US
dc.contributor.authorEbert, D.en_US
dc.contributor.authorEichmann, P.en_US
dc.contributor.authorGalakatos, A.en_US
dc.contributor.authorHattasch, B.en_US
dc.contributor.authorIlkhechi, A.en_US
dc.contributor.authorKraska, T.en_US
dc.contributor.authorShang, Z.en_US
dc.contributor.authorTromba, I.en_US
dc.contributor.authorUsta, Arifen_US
dc.contributor.authorUtama, P.en_US
dc.contributor.authorUpfal, E.en_US
dc.contributor.authorWang, L.en_US
dc.contributor.authorWeir, N.en_US
dc.contributor.authorZeleznik, R.en_US
dc.contributor.authorZgraggen, E.en_US
dc.contributor.editorCastellanos, M.
dc.contributor.editorChrysanthis, P.
dc.contributor.editorPelechrinis, K.
dc.coverage.spatialMunich, Germanyen_US
dc.date.accessioned2020-02-19T10:17:48Z
dc.date.available2020-02-19T10:17:48Z
dc.date.issued2019
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 28 August-1 September 2017en_US
dc.descriptionConference Name: 11th International Workshop on Real-Time Business Intelligence and Analytics, BIRTE 2017en_US
dc.description.abstractEnabling interactive visualization over new datasets at “human speed” is key to democratizing data science and maximizing human productivity. In this work, we first argue why existing analytics infrastructures do not support interactive data exploration and outline the challenges and opportunities of building a system specifically designed for interactive data exploration. Furthermore, we present the results of building IDEA, a new type of system for interactive data exploration that is specifically designed to integrate seamlessly with existing data management landscapes and allow users to explore their data instantly without expensive data preparation costs. Finally, we discuss other important considerations for interactive data exploration systems including benchmarking, natural language interfaces, as well as interactive machine learning.en_US
dc.identifier.doi10.1007/978-3-030-24124-7_11en_US
dc.identifier.doi10.1007/978-3-030-24124-7en_US
dc.identifier.eisbn9783030241247
dc.identifier.isbn9783030241230
dc.identifier.issn1865-1348
dc.identifier.urihttp://hdl.handle.net/11693/53434
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.ispartofReal-time business intelligence and analyticsen_US
dc.relation.isversionofhttps://dx.doi.org/10.1007/978-3-030-24124-7_11en_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-030-24124-7en_US
dc.source.titleLecture Notes in Business Information Processingen_US
dc.subjectBig dataen_US
dc.subjectInteractive data explorationen_US
dc.subjectInteractive visualizationen_US
dc.subjectIDEAen_US
dc.subjectInteractive machine learningen_US
dc.subjectData analyticsen_US
dc.titleTowards interactive data explorationen_US
dc.typeConference Paperen_US

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