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1、TOPTENBigDataTRENDSFOR2017Top10BigDataTrendsfor20172016wasalandmarkyearforbigdatawithmoreorganizationsstoring,processing,andextractingvaluefromdataofallformsandsizes.In2017,systemsthatsupportlargevolumesofbothstructuredandunstructureddatawillcontinuetorise.Themarketwilldemandplatformsthathe
2、lpdatacustodiansgovernandsecurebigdatawhileempoweringenduserstoanalyzeEachyearatTableau,thatdata.ThesesystemswillmaturetooperatewellinsideofwestartaconversationenterpriseITsystemsandstandards.aboutwhat’shappeningintheindustry.Thediscussiondrivesourlistofthetopbig-datatrendsforthefollowingye
3、ar.Theseareourpredictionsfor2017.Bigdatabecomesfastandapproachable:OptionsexpandtospeedupHadoop1Sure,youcanperformmachinelearningandconductsentimentanalysisonHadoop,butthefirstquestionpeopleoftenaskis:HowfastistheinteractiveSQL?SQL,afterall,istheconduittobusinessuserswhowanttouseHadoopdataf
4、orfaster,morerepeatableKPIdashboardsaswellasexploratoryanalysis.ThisneedforspeedhasfueledtheadoptionoffasterdatabaseslikeExasolandMemSQL,Hadoop-basedstoreslikeKudu,andtechnologiesthatenablefasterqueries.UsingSQL-on-Hadoopengines(ApacheImpala,HiveLLAP,Presto,Phoenix,andDrill)andOLAP-on-Hadoo
5、ptechnologies(AtScale,JethroData,andKyvosInsights),thesequeryacceleratorsarefurtherblurringthelinesbetweentraditionalwarehousesandtheworldofbigdata.FURTHERREADING:AtScaleBIonHadoopbenchmarkQ42016BigdatanolongerjustHadoop:Purpose-builttoolsforHadoop2becomeobsoleteInpreviousyears,wesawseveral
6、technologiesrisewiththebig-datawavetofulfilltheneedforanalyticsonHadoop.Butenterpriseswithcomplex,heterogeneousenvironmentsnolongerwanttoadoptasiloedBIaccesspointjustforonedatasource(Hadoop).Answerstotheirquestionsareburiedinahostofsourcesrangingfromsystemsofrecordtocloudwarehouses,tostruct
7、uredandunstructureddatafrombothHadoopandnon-Hadoopsources.(Incidentally,evenrelationaldatabasesarebecomingbigdata-ready.SQLServer2016,forinstance,recentlyaddedJSONsupport.)In2017,customerswilldemandanalyticsonalldata.Platformsthataredata-andsource-agnost
