!!!!!!!!!! Big!Data!Revealed!! An!Information!Difference!Research!Study!! December!2013!!!!!!!!!!!! Sponsored!by!!!!!!!!!!!!!

Size: px
Start display at page:

Download "!!!!!!!!!! Big!Data!Revealed!! An!Information!Difference!Research!Study!! December!2013!!!!!!!!!!!! Sponsored!by!!!!!!!!!!!!!"

Transcription

1 BigDataRevealed AnInformationDifferenceResearchStudy December2013 Sponsoredby

2 TABLEOFCONTENTS Big$Data$Revealed$ 2$ EXECUTIVE$SUMMARY$...$4 BACKGROUND$TO$THE$SURVEY$...$6 THE$APPROACH$...$6 ABOUT$THE$RESPONDENTS$...$7 ADOPTION$OF$BIG$DATA$...$8 LEADERSHIP$AND$FOCUS$...$10 KEY$BENEFITS$AND$SUCCESS$FACTORS$...$12 BIG$DATA$DOMAINS$...$15 COSTS$AND$SIZE$OF$BIG$DATA$...$16 TECHNOLOGIES$DEPLOYED$...$18 ADDITIONAL$FEEDBACK$...$19 CONCLUSIONS$...$21 ENTERPRISES...21 VENDORS...22 ABOUT$THE$INFORMATION$DIFFERENCE$...$23 QUESTIONNAIRE$...$24 Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

3 Big$Data$Revealed$ 3$ LISTOFFIGURES Figure'1' 'Respondents'by'Company'Revenue'...'7 Figure'2' 'Respondents'by'Job'Function'...'7 Figure'3' 'Respondents'by'Industry'Sector'...'8 Figure'4' 'Status'of'Big'Data'in'Organizations'...'9 Figure'5' 'Reasons'for'Implementing'Big'Data'...'9 Figure'6' 'Primary'Focus'for'Big'Data'in'Business'...'10 Figure'7' 'Business'areas'leading'Big'Data'Initiatives'...'11 Figure'8' 'Responsible'for'Big'Data'in'the'Organization'...'11 Figure'9' 'Benefits'from'Big'Data'Initiatives'...'12 Figure'10' 'The'Main'Roadblocks'for'Big'Data'Initiatives'...'13 Figure'11' 'Positioning'of'Big'Data'and'Data'Management'Initiatives'...'13 Figure'12' 'Data'Management'Initiatives'in'Organizations'...'14 Figure'13' 'Critical'for'Success'with'Big'Data'...'14 Figure'14' 'Is'Big'Data'focused'on'Data'from'Web'Applications'...'15 Figure'15' 'Key'Big'Data'Domains'...'15 Figure'16' 'Focus'on'Structured'or'Unstructured'Big'Data'...'16 Figure'17' 'Volumes'of'Big'Data'Handled'...'17 Figure'18' 'Expenditure'on'Big'Data'to'Date'...'17 Figure'19' 'Planned'Expenditure'on'Big'Data'next'Year'...'18 Figure'20' 'Software'Solutions'Deployed'(or'Planned)'...'18 Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

4 EXECUTIVESUMMARY Big$Data$Revealed$ 4$ TherehasbeenagreatdealofrecentinterestintheindustryabouthowtodealwithsoQcalledBig Data,whichisdefinedasfollows: Definition:Big$Data$is$the$term$applied$to$data$sets$whose$size$is$beyond$the$ability$of$ commonly$used$software$tools$to$capture,$manage,$and$process$the$data$within$a$tolerable$ elapsed$time.$(source:$wikipedia). AlthoughBigDatahasrecentlyreceivedwidepressattention,thereisstillsurprisinglylittleconcrete informationavailableregardingthestateofbigdatainitiativesinbusiness.forexample,howmany companieshaveactuallyimplementedbigdatatechnologies,andinwhatareas;howmuchmoney andeffortareorganizationsinvestinginit;whichpartsofthebusinessaredrivingbigdata investments;whatbenefitsaretheyseeing;andwhichdatavolumesarebeinghandled?this survey,whichwassponsoredbyhelpitandteradata,aimstoaddressthesequestions. Themainfindingsfromthesurvey,basedon178responses,aresummarizedbelow: 30%currentlyhavenoplanstoimplementBigData,27%currentlylivewiththeirBigData initiative,andafurther5%areabouttogolive.thiscompareswellwiththefindingsfromour previoussurveyof24%.24%nowplantogolivenextyear. The27%liveimplementationssplitsoutregionallyasfollows:NorthAmerica(includingCanada) 6%,Europe18%,andtherestoftheworld3%.Thisresultfliesinthefaceofconventional wisdomthatsuggeststhatnorthamericaiswellaheadinbigdata. 24%wanttobeabletoanalyzeverylargedatasets.Theredoesnotappeartobeadominant themeastothereasonsforimplementingbigdataprojects. Thefocusisonimprovingthequalityofdecisionmaking(39%),followedbymeetingcustomer needs(apoorsecondat19%). ITisclearlyinthedrivingseat(33%)withregardstoBigDataprojects. TheCIOisgenerallyresponsibleforandleadingBigDatainitiatives(31%). 13%haveidentifiednewbusinessopportunitieswiththeirBigDatainitiatives.Thisleadsusto concludethatitisstillearlydayswhenitcomestobigdata. Themainroadblocktoimplementationisthatitisdifficulttopresentabusinesscase. Encouragingly,45%reportedthattheirBigDatainitiativeisorwillbeapartoftheirwiderdata managementinitiativessuchasmdm. Managementunderstandingandawareness(42%),leadershipattheCxOlevel(18%)anda soundandwellqdocumentedbusinesscase(9%)areallcitedascriticaltosuccessful implementationofbigdatainitiatives.thissuggeststhereiscurrentlyalackofsufficientbuyqin andcommitmentfromthebusinessside. BigDataisnotmainlyfocusedonanalyzingdatacollectedfromwebQbasedapplications(52%). Customerdataisthemostsignificantdomainformostorganizations,withproductdatasecond andfinancialdatathird.soorganizationsarenotjustinterestedinanalyzingtwitterfeeds. 40%claimedthatitistheirintentiontouseHadooptechnologiesasthestagingareaforalltheir datainfuture. Themajorityofthedataisintherange1to10terabytes.5%reporteddatavolumesinthe petabyterange,withjust4%inthe200terabyteto1petabyterange.itwouldseemthatbig Dataisnotnecessarilythatlarge. 8%havespentover$5millionontheirBigDatainitiativewhile42%havespentlessthan$1 million,25%lessthan$100,000.thisfurthersuggeststhatbigdataisatanearlystageinmost companies. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

5 Big$Data$Revealed$ 5$ 11%plantospendmorethan$5millionwhile32%plantospendlessthan$1millioninthe comingyear.13%willspendlessthan$100,000. ThemostpopularthreetechnologiesdeployedareMicrosoft,Oracle,andTeradata,butthereis nodominanttechnologyreportedbythesurveyrespondents. Respondentfeedbackindicatesthatthereisadealofscepticismabouttheneedforbusiness case,viability,andpracticalimplementationofbigdata. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

6 BACKGROUNDTOTHESURVEY Big$Data$Revealed$ 6$ TherehasbeenagreatdealofrecentinterestintheindustryabouthowtodealwithsoQcalledBig Data,whichisdefinedasfollows: Definition:Big$Data$is$the$term$applied$to$data$sets$whose$size$is$beyond$the$ability$of$ commonly$used$software$tools$to$capture,$manage,$and$process$the$data$within$a$tolerable$ elapsed$time.$(source:$wikipedia). AlthoughBigDatahasrecentlyreceivedwidepressattention,thereisstillsurprisinglylittleconcrete informationavailableregardingthestateofbigdatainitiativesinbusiness.webelievethetimeis ripetosurveythisareaindepth.inparticular,wewanttoputhardnumbersaroundsomequestions including: HowmanycompanieshaveactuallyimplementedBigDatatechnologies,andinwhatareas? Howmuchmoneyandeffortareorganizationsinvestinginit? WhichpartsofthebusinessaredrivingBigDatainvestments? Whatbenefitsaretheyseeing? Whichdatavolumesarebeinghandled? THEAPPROACH TheInformationDifferencesurvey, Big%Data%Revealed,wasconductedovertheInternetduring theperiodoctobertonovember2013.theparticipantswereselectedby invitations originatingdirectlyfromtheinformationdifference.participationwasalsopossibleviaalinkfrom TheInformationDifferenceLtd.websiteandvialinksonLinkedIn. ThesurveywastargetedatseniorbusinessandITleadersworldwide,drawnfromlarger organizations(withrevenuesgreaterthanus$1billionannually). Theparticipantswereprovidedwiththefollowinginformationpriortocompletingthesurvey: There$has$been$a$great$deal$of$recent$interest$in$the$industry$about$how$to$deal$with$soBcalled$Big$ Data,$which$is$defined$as$follows:$ Big$Data$is$the$term$applied$to$data$sets$whose$size$is$beyond$the$ ability$of$commonly$used$software$tools$to$capture,$manage,$and$process$the$data$within$a$tolerable$ elapsed$time.$$(source:$wikipedia) $$ $ Despite$the$plethora$of$press$attention,$there$is$still$surprisingly$little$concrete$information$available$ regarding$the$state$of$big$data$initiatives$in$business.$$at$the$information$difference,$we$consider$the$ time$ripe$to$survey$this$area.$$ $ All$information$provided$will$be$used$in$aggregate$form$only$and$will$be$kept$strictly$confidential.$$ The$survey$has$only$20$questions$on$the$topic$and$should$not$take$more$than$10$minutes$to$complete.$ In$return$for$a$fully$completed$survey,$you$will$receive$a$free$summary$of$the$analysis$of$the$survey$ results.$$additionally,$your$name$will$be$entered$in$a$prize$draw$and$the$first$five$winners$will$receive$ a$free$vendor$profile$(worth$$495)$of$their$choice.$$we$will$also$make$a$$2$contribution$to$the$red$ Cross$for$each$fully$completed$survey.$ ThequestionnaireisappendedinthesectionheadedQuestionnaire. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

7 ABOUTTHERESPONDENTS Big$Data$Revealed$ 7$ Atotalof178respondentsworldwidetookthesurvey.34%werefromNorthAmerica(including Canada),43%fromEuropeandtheremainder(22%)fromtherestoftheworld. 52%oftherespondentswerefromlargerorganizationswithannualrevenuesinexcessofUS$1 billion.some21%werefromorganizationswhoseannualrevenuelastyearwasgreaterthanus$10 billion.48%werefromcompanieswithannualrevenuesbelowus$1billion.thisrepresentsa balancedmixofbothlargerandsmallorganizations.thedetailedbreakdownisshownasfigure1. Figure$1$ $Respondents$by$Company$Revenue$ Some42%oftherespondentsweredrawnfromabusinessbackgroundwiththemajorityhavingan ITrole(58%).ThislikelyreflectsthecurrentfocusofBigDatainthemediatowardstheIT community.22%hadjobtitlesatthedirectorleveloraboveand27%hadthetitleofenterprise Architect.ThedetailsaresetoutinFigure2. Figure$2$ $Respondents$by$Job$Function$ Thelargestlevelofparticipationwasfromthebanking,insurance,andfinancialservicesindustry (22%),perhaps,supportingtheviewthatthefinancialsectorisseekingnewbusinessopportunities tohelpitemergefromthefinancialcrisis.thefinancialsectorwasthelargestverticalofthe businessrespondentswithretailandpharmaceuticals/biotech/healthcarebothcominginat9%. Incontrasttoourprevioussurvey 1 theprofessionalservicesandcomputingsectors(32%)wereonly representedatacombinedlevelof10%.thisearliersurveyshowedthatthemainfocusandinterest 1 DoesBigDatameanBigMDM?,InformationDifferenceResearchReport,November2012 Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

8 Big$Data$Revealed$ 8$ appearedtocomefromtheitsector.thepresentresultswouldindicateashiftofinteresttothe businessintheformofthefinancialsector. OthersincludedEQCommerceandRecruitment(7%).Theremainderrepresentsawiderangeof industrysectors.thefullresultsareshowninfigure3. Figure$3$ $Respondents$by$Industry$Sector$ Theanalysisoftheresultsfromthesurveyispresentedbelow.Thequestionsreferredtointhetext areindicatedas[qn]andaresetoutinfullintheappendixheaded Questionnaire. Apartfromtheexceptionsmentionedinthetext,analysisoftheresultsfromthesurveyforregional dependencies forexample,comparisonsbetweeneuropeandnorthamerica didnotyieldany statisticallysignificantdifferencesortrends. ADOPTIONOFBIGDATA Theburningquestionwas:HowmanyorganizationsareactuallyalreadyupandrunningwithliveBig Dataimplementations?Weaskedrespondents[Q1]tosharewithuswhethertheyhadlive initiativesorwereplanningtoimplementbigdatawithinthecomingyear.theresultsare summarizedinfigure4. Some30%toldusthattheyhavecurrentlynoplanstoimplementBigDataintheirorganizations. Surprisingly,27%reportedthattheyarecurrentlylivewiththeirBigDatainitiative,andafurther5% areabouttogolive.thisisverysimilartothefindingsfromourprevioussurvey(24%)andsuggests thattherehasbeenrelativelylittlerealprogressintermsoftheproportionofcompanies implementingitsince2012.afurther24%plantogolivenextyear.takentogether,giventhislevel ofinterest,itwouldseemthatbigdataisbeginningtobetakenseriouslybyorganizations. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

9 Big$Data$Revealed$ 9$ Lookingingreaterdetailatthe27%ofliveimplementations,wefindthatthissplitsoutregionallyas follows:northamerica(includingcanada)6%,europe18%andtherestoftheworld3%. Figure$4$ $Status$of$Big$Data$in$Organizations$ ThisresultfliesinthefaceofconventionalwisdomthatsuggeststhatNorthAmericaiswellahead. Certainly,anecdotalevidencehasbeenthattheUSAhasbeenfaraheadofEuropeintermsofBig DatatakeQup,especiallyasthingslikewebmarketinganalyticsandsocialmediawerereallythe pioneersofhadoop.giventhat34%ofrespondentsweredrawnfromnorthamerica,compared with43%fromeurope,itcannotreasonablybeconcludedthatthisdifferencecanbewhollyascribed tothedifferenceinsamplesizes.ifweturnourattentiontothefutureplans,thenhereagainwe seeaslightlyhigherleveloftakeupineurope(althoughmuchlessmarkedthanforlive implementations).ofatotalof42%eitherabouttogoliveorplanned,13%werefromnorth America,16%fromEurope,and12%fromtherestoftheworld.MightitbethatEuropehasmore interestinthesubjectthaniswidelyperceived,andthatvendorswoulddowelltofocusontheir Europeancustomerbase? WethenaskedrespondentstotelluswhytheywereconsideringorhadinitiatedtheirBigData initiative[q2].theresultsaresetoutinfigure5. Figure$5$ $Reasons$for$Implementing$Big$Data$ Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

10 Big$Data$Revealed$ 10$ Some24%areclearthattheywanttobeabletoanalyzeverylargedatasets.Whilethisclearly makessensethereisawiderangeofbusinessdemandsforbigdata.theredoesnotappeartobea dominanttheme.interestingly Other isthesecondlargestcategory(16%)andincludes requirementssuchas: TodealwithCustomerRequestsforResearch Tocopewithalargeincreaseincustomers WewanttoanalyzegeoQdataaspartofourriskassessment AnalyzinggenomicandotherpatientQrelateddata Tostoremedicalclaim837data. Afurther37%dividedroughlyequallybetweentheabilitytobeabletoanalyzeweblogs(13%), financialtransactions(12%),andclickqstreamdata(12%).sothebroadfocusisondealingwithvery largedatasetsingeneral,withawiderangeofspecificdrivers. LEADERSHIPANDFOCUS SowhatisthefocusforBigDatainitiativesinmostorganizationsandwhoisleadingthese initiatives?wefirstaskedabouttheprimaryfocusforbigdatainitiativesintheirorganizations[q3]. TheresultsareshowninFigure6. Figure$6$ $Primary$Focus$for$Big$Data$in$Business$ Interestingly,themainfocusisonimprovingthequalityofdecisionmaking(39%),withmeeting customerneedsapoorsecond(19%).itisintriguingthatcostreductionappearstohavebeen relegatedtoalowerpriority(8%)and,rathersurprisingly,managementofriskcomesinatamere 5%.Other(whichaccountsfor13%)included:enhancesales;exploringall(customers,fraud,risk, newbusinessopportunities);identifying"best"prospectsformarketingcampaigns;increasingthe customerexperience;etc. WenextaskedrespondentswhatareasoftheirbusinesswereleadingtheBigDatainitiative[Q4]? TheresultsareshowninFigure7. ItisperhapssurprisingthatITissoclearlyinthedrivingseat(33%)giventhefactthatcostreduction (seeabove)onlycameinat8%.maybethissuggeststhatitandbusinessaregenerallystartingto workclosertogether.almostaquarter(24%)oftheinitiativesarebeingledbycustomerservices, whichsquaresupwiththeprevioushighfocuson meetingcustomerneeds (19%). Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

11 Big$Data$Revealed$ 11$ Figure$7$ $Business$areas$leading$Big$Data$Initiatives$ Otherareasrated16%included:Drilling,ExploringviaIT,FraudandFinance. WhointhebusinessisactuallyresponsibleforBigDataintheorganizationandforleadingthe initiatives[q10]?theresponsesfromtherespondentsaresetoutinfigure8. Figure$8$ $Responsible$for$Big$Data$in$the$Organization$ Inlightofthepreviousresult,itisperhapsunsurprisingthattheCIOisinthedrivingseatwhenit comestoresponsibilityforandtheleadingofbigdatainitiatives(31%).aseniorbusinessmanager isdrivinginlessthanaquarteroforganizations(22%).thissuggeststhatmanyoftheinitiativesare originatingfromtheitsideofthebusinessandthat,inturn,suggeststhattheremaybeissueswith definingaclearbusinesscase. Other(12%)included:ITManager,LeadR&Dmanager, Nooneisnamedortherearemany leaders, Responsibilityisnotdefinedatthetimebeing,VPInformationSystems,chiefmarketing officer,and nosingleperson. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

12 KEYBENEFITSANDSUCCESSFACTORS Big$Data$Revealed$ 12$ Whatkeybenefitsareorganizationsseekingandwhatroadblocksdotheyidentifyhampering progress?howdoestheirbigdatainitiativerelatetootherinitiativessuchasmasterdata management(mdm),dataquality,anddatagovernance? Weaskedrespondents,iftheyalreadyhadaBigDatainitiatelive,whatbenefitstheyhadrealizedto date[q14]?theirresponsesaresummarizednfigure9. Figure$9$ $Benefits$from$Big$Data$Initiatives$ Whilesome(13%)claimedtohaveidentifiednewbusinessopportunities,othersreportedimproved operationalefficiency(11%),whileoverhalfoftherespondentsdidn'tknowatthistime.this stronglysuggeststhatdespitetheapparentnumberof live implementations,therewasasyetno resoundingwinnerforbenefits.thisleadsustoconcludethatitstillearlydays. Whatarethemainroadblocksencounteredbyorganizations[Q9]?Figure10showstheresults. Respondentswereaskedtoselectuptothreeoptions,sotheresultsarenotadditive.Themain conclusionappearstobethatitisdifficulttopresentabusinesscase.perhapsweshouldreferback tofigures7and8aboveandviewthisresultinthelightofthestrongleadershipbyit(33%)inmany oftheinitiatives.thereisastrongsuggestionthatlackofclearleadershipfromthebusinessside maybetherootcauseofthedifficultyinpreparingaconvincingbusinesscase.thisisreinforced whenweconsiderthatthesecondmostselectedoptionisthatthereisalackofclearunderstanding ofthebusinessobjectives.onecouldbeforgivenforconcludingthatitwouldbegoodtoapplythe principleof morehastelessspeed tomanyoftheinitiatives.oneisforcedtotheconclusionthat inmanycases,initiativeshavebeenstartedwithoutclearbusinessbuyqinandbusinessgoals.isthe currentmediahypearoundbigdatacausingorganizationstojumptooquicklyandillqpreparedly intotheseinitiatives? IsitpossiblethatorganizationsarejumpingintoBigDatainitiativestooearlyandbeforetheyhave paidadequateattentiontotheirdataqualityanddatagovernance? Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

13 Big$Data$Revealed$ 13$ Figure$10$ $The$Main$Roadblocks$for$Big$Data$Initiatives$ WeaskedrespondentstosharewithushowtheircurrentorproposedBigDatainitiativewas positionedwithregardtotheirotherdatamanagementinitiatives[q16].theresultsaresetoutin Figure11. Figure$11$ $Positioning$of$Big$Data$and$Data$Management$Initiatives$ Veryencouragingly,45%reportedthattheirBigDatainitiativeisorwillbeapartoftheirwiderdata managementinitiativessuchasmdm.however,thisresultneedstobeinterpretedagainstthe Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

14 Big$Data$Revealed$ 14$ backgroundofwhichdatamanagementinitiativestheyhavealreadyimplemented.weasked respondentstotellusabouttheirdatamanagementlandscape[q17].theresultsaresetoutin Figure12. Figure$12$ $Data$Management$Initiatives$in$Organizations$ Itisverypositivethatmorethanhalfofalltheorganizationshaveinfactimplementeddata managementacrosstheboard.surprisingly,54%toldustheyalreadyhavedatagovernance,which isencouragingsincethisbecamecommonlyavailablemuchlaterthanmasterdatamanagement (MDM)anddataquality.Clearly,wearehalfwaythereandthereisstillalongwaytogoinadopting fulldatamanagement.itisveryencouragingthatsomanyorganizationsseebigdataasintegralto theirotherdatamanagementinitiatives. WhatdoorganizationsbelieveiscriticaltosuccesswithBigDatainitiatives[Q18]?Theresponses aresummarizedinfigure13. Figure$13$ $Critical$for$Success$with$Big$Data$ Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

15 Big$Data$Revealed$ 15$ TheresponsesherearereallyallfocusedaroundsecuringbusinessbuyQin.Management understandingandawareness(42%),leadershipatthecxolevel(18%),andasoundandwellq documentedbusinesscase(9%)allunderlinethefactthatthereiscurrentlyalackofsufficientbuyq inandcommitmentfromthebusinessside.thehighlevelofleadershipandinvolvementfromit reportedfurthersupportsthisconclusion.wewouldsuggestthatthebusinesswouldlargelyappear tobe sittingonthefence atthemomentasfarasbigdataisconcerned. BIGDATADOMAINS SowhatdoorganizationsbelieveisBigDataandwhichdatadomainsareofimportanceforthem? WefirstaskedwhetherBigDatawasmainlyfocusedonanalyzingdatacollectedfromwebQbased applications[q5].theresponsesweremixedwithaheftynofrom52%,butwithafurther36% reportingthatitismostlyaboutwebqbasedapplicationdata.some9%consideredbigdatatobe exclusivelyaboutwebqbasedapplicationdata.theresultsareshowninfigure14. Figure$14$ $Is$Big$Data$focused$on$Data$from$Web$Applications$ Morethananything,theseresultsagainsupportthefactthatthereareclearlymultipledriversfor BigData.WethenaskedrespondentstotelluswhichdatadomainswerekeytotheirBigData initiatives[q6].theresultsareshowninfigure15. Figure$15$ $Key$Big$Data$Domains$ Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

16 Big$Data$Revealed$ 16$ Respondentswereaskedtoselectalldomainsthatappliedfortheirbusinesssotheresultshereare notadditive.customerdataclearlyisthemostsignificantdomainformostorganizationswith productdatasecondandfinancialdatathird interestingly,bothafterunstructureddata,whichis clearlygainingininterest.theoveralltrendisverymuchinlinewithwhatwehavefoundreported formdmdatadomainsinprevioussurveys. 2 Thereferencetounstructureddatainthepreviousquestionisfurthersupportedbyresponsesto ournextquestionrelatingtowhethertheirbigdatainitiativewasfocusedonstructuredor unstructureddata[q7].theresponsesaresummarizedasfigure16. Figure$16$ $Focus$on$Structured$or$Unstructured$Big$Data$ AscanbeseenfromFigure16,theresponsewasaresounding both.soclearlyorganizationsare notjustinterestedinanalyzingtwitterfeeds. TherehasbeenincreasinginterestinthemediaintheuseofHadoopQtypetechnologiesasthe stagingarea foralldatapriortopassingitontootherdatastoressuchasdatawarehousesor OLAPcubes.WeaskedourrespondentstosharewithustheirviewsonthisuseofHadoop[Q8].A resounding40%claimedthatitisindeedtheirintentiontousehadooptechnologiesasthestaging areaforalltheirdatainfuture(priortoloadingitintodatawarehousesorolapcubes).lessthana thirddonotplantodoso,andaboutoneqthirddoesn tknowatthisstage.thisisakeyresultforthe conventionaletlvendors,whoneedeithertoadapttheirtechnologiesorembracehadoopinthe nearfuture.otherwise,wesuspecttheywillfaceincreasingdifficulties. COSTSANDSIZEOFBIGDATA SohowbigisBigDataandwhatareorganizationsspendinginthisarea?Wefirstlyasked respondentstotellusaboutthemaximumvolumeofdatatheyarecurrentlyhandling(orplanning tohandle)intheirbigdatainitiative[q11].thefeedbackfromtherespondentsissetoutinfigure 17. Fromtheresultsreported,itisclearthatthemajorityofthedataisintherange1to10terabytes. Only5%arereportingdatavolumesinthepetabyterange,withonly4%inthe200terabyteto1 petabyterange.perhapsweshouldbereferringto quitebigdata ratherthanbigdata.itis surprisingthatthemostpopularresultliesinthe1to10terabyterange,suggestingthatcomplexity ratherthansheersizemaybethekeydriver. WethenturnedourattentiontowhatorganizationswerespendingorplanningtospendontheirBig Datainitiatives. 2 MDMMarketResearchSurvey,InformationDifferenceResearchReport,July2012 Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

17 Big$Data$Revealed$ 17$ Figure$17$ $Volumes$of$Big$Data$Handled$ WhatisBigDatacosting?WeaskedorganizationswhattheyhavespenttodateontheirBigData initiatives[q13].theexpenditurerangeissetoutinfigure18. Figure$18$ $Expenditure$on$Big$Data$to$Date$ WealsoaskedwhattheyplantospendonBigDatainthecomingyear[Q12]?Theexpenditure rangeissetoutinfigure19.onlysome8%havespentover$5million,while42%havespentless than$1million,25%lessthan$100,000.thissuggeststhatitisstillveryearlyformostbigdata initiativeswithrelativelymodestoutlaystodate.roughlyathirdeitherdon'tknoworhavespent nothing. Turningtotheirplannedexpenditureoverthenexttwelvemonths,11%plantospendmorethan$5 millionwhile32%plantospendlessthan$1million.13%willspendlessthan$100,000.whilethis suggestsaslightincreaseinplannedexpenditureoverthecomingtwelvemonths,itisnotamajor commitment.thisleadsustoconcludethatbigdataisstillintheearlydaysofbeingadopted,with manyorganizationsperhapstestingthetemperatureofthewaterwithrelativelylimited expenditure. ItseemsfairtoconcludethatBigDatahassomewaytogobeforeitreacheseventhefirststagesof maturity. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

18 Big$Data$Revealed$ 18$ Figure$19$ $Planned$Expenditure$on$Big$Data$next$Year$ TECHNOLOGIESDEPLOYED WhattechnologiesarebeingdeployedbyorganizationsfortheirBigDatainitiatives?Weasked respondentstoindicatewhichofthecurrentrangeofsoftwaretoolsforbigdatatheyeitherhad deployedorplannedtouse[q15].theresultsarepresentedasfigure20. Figure$20$ $Software$Solutions$Deployed$(or$Planned)$ Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

19 Big$Data$Revealed$ 19$ Therespondentswereaskedtoselectallthatapplied,sotheresultsarenotadditiveanddonot representmarketshare. ThemostpopularthreeappeartobeMicrosoft,Oracle,andTeradata.Mostoftheremainderhave beendeployedorplannedbyasmallernumberoforganizations.itisinterestingtonotethatkey vendorssuchashortonworks,mapr,andjaspersoftdonotfigurehighonthislist.perhapsthisis becauseinthefirstinstance,organizationshaveturnedtotheircurrentsoftwaresuppliersto providebigdatasolutions.weseethisasalikelyfuturetrendwithbusinessexpectingtheirhouse vendor,beitsap,ibm,microsoft,informatica,ororacle,toprovideabigdatasolution. Othersoftwaresolutionsmentionedincluded:AWSRedshift,Cassandra,Causata,Infobright, QlikView,andSAS. ADDITIONALFEEDBACK Finally,weaskedrespondentstoprovideanyadditionalviewsorcommentsthattheyhadinregard totheroleofbigdataintheirorganization[q19].theirextensivefeedbackincluded: Asofnowit(ourBigDatainitiative)isbeingusedasahugearchivalsystemforalltransaction dataforfurtheranalysis. BigDataisnotonlyabouthavingaHadoopcluster BigDataseemstobebuzzwordonlyforus needstobemoreconcrete. Bigdataisandwillbemoreimportant. DatagovernanceandgoodqualityandaccuratedataiskeyfordecisionQmakingprocesses. Idon'tthinkBigDatawillhelporganizationsintheanalyticsarea. Itisallaquestionoffurthertrialanderror ItwillhaveakeyroleinourInformationmanagement. It'sasolutionlookingforaprobleminmanycases. Itisacrucialpartoffinancialreportingandcontrolling. Lotsofmovingpartswithevolvingusecases Sponsorshipneeded. Theabilitytoseparatethe BigNoise from BigData willbecrucialforthesuccess. Toosoontoknowwhattheproperapproachis. Weneedeasyinstructions. Wearestillintheexperimentalstage,learningthetechnologies. Wewilldevelopourowntools. BigDataisaparadigmshiftinITthinkingandbusinessneedstobecontinuouslyinvolvedas implementationpartner. OrganizationswithimmatureBI/DGwilleventuallymakeahuge,costlyerroneousdecisionthat noonecouldhavepredicted alataleb'sblackswanwarning. WenothaveaBigDatainitiativeinternaltotheorganization,butarecreatingofferingsforour customers. Wesimplyhaven tidentifiedausecaseyet itisn'tneeded,andourcurrentprocessessuffice. Difficulttofindagoodbusinessusecaseforitandthenbeabletodemonstratethevalueina costqeffectiveway. ThekeychallengewillbetointegrateBigDatawithexistinginternaldatasources.Sodata integrationanddataqualityarecriticalenablers. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

20 Big$Data$Revealed$ 20$ OurBigDatausecaseexists,butitisanevolutionarystepandrequirescommitmentfromend customerstoimplement. Understandtheopportunities,havealongtermstrategy,futureprooftheorganization,gain executivesupport,createbusinesscaseandjustification,startwithlowhangingfruitlike operationalefficiencies. Asabusinessuser,questionsregardingdatasizearecompletelyirrelevant.I'minterestedin capabilities thetechchoicesarenotofinterest WearetryingtoworkwithourmarketingareaandMedicalInformaticsareatofindan appropriatebusinesscaseforbigdata.wearegoingtolookatweblogsandanalyzelargedata setstodosomehealthcarepredictivemodeling. Thekeygoalispredictiveanalyticsappliedtomachinedata,maintenanceeventdataand operationaldatainordertounderstandandpredictlargefleetperformanceandoptimizethe maintenanceregime. Atthismoment,thereareveryfewpeoplewhocanreallyanalyzetheBigDataparadigm withoutbeingcarriedawaybythehype.itiscrucialtoknowhowit'sgoingtohelpyour particularbusinesscaseinsteadoftryingtobeonthelatestbandwagon. Beforeyoustart,youneedtounderstandhowyouwillmanageBigData,andthescalabilityof yoursolution. BigdatainahealthcaresettingismaybeofadifferentproportionthanBigDataasit'sdefinedin theworldoftelco,socialmedia,etc.,butit'sreallybig. BigDataisanextensionofourBI/DataWarehousingprogram.BigDataextendsexistingoptions byopeningupadepthofdata.bigdatatoolsalsoopenthedoorfornewtypesofanalytical techniques. WeareexploringBigData,andtryingtounderstandhowitmaybeappliedandwhatbenefitsit wouldprovideforourbusiness. BDisnotmature,yetsomebonafidesuccessesaredemonstrated adifficultcombinationto sell.further,westillhavewaystogowithclassicrdbmsdata:dq,dg,etc. Itisclearfromtherespondentfeedbackabovethatthereisadealofskepticismabouttheneedfor, businesscase,viabilityandpracticalimplementationofbigdata. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

21 Big$Data$Revealed$ 21$ CONCLUSIONS Keyconclusionsandrecommendationsresultingfromthesurveyanalysisaresummarizedbelow. Thesehavebeensplitintotwogroups:thoseofdirectrelevancetoenterprisesandorganizations consideringorintheprocessofimplementing(orwhohavealreadyimplemented)bigdata initiatives,andthoserelatingtothesoftwarevendorsandsystemsintegrators(sis). Enterprises$ 30%toldusthattheycurrentlyhavenoplanstoimplementBigData.27%reportedthatthey arecurrentlylivewiththeirbigdatainitiative,andafurther5%areabouttogolive.this compareswellwiththefindingsfromourprevioussurvey(24%),andsuggeststhattherehas beenrelativelylittleprogresssince2012.afurther24%plantogolivenextyear. The27%liveimplementationssplitoutregionallyasfollows:NorthAmerica(includingCanada) 6%,Europe18%,andtherestoftheworld3%.Thisresultfliesinthefaceofconventional wisdomthatsuggeststhatnorthamericaiswellahead. 24%wantstobeabletoanalyzeverylargedatasets.Clearly,thereisawiderangeofbusiness demandsforbigdata.theredoesnotappeartobeadominanttheme. Themainfocusisonimprovingthequalityofdecisionmaking(39%),withmeetingcustomer needsapoorsecond(19%). ITisclearlyinthedrivingseat(33%).Almostaquarter(24%)oftheinitiativesarebeingledby CustomerServices. GiventhepreviousresultitisperhapsunsurprisingthattheCIOisinthedrivingseatas responsibleforandleadingbigdatainitiatives(31%). Some13%claimedtohaveidentifiednewbusinessopportunitieswiththeirBigDatainitiatives. Othersreportedimprovedoperationalefficiency(11%)whileoverhalfoftherespondentsdidn't knowatthistime.thisstronglysuggeststhatdespitetheapparentnumberof live implementations,therewasasyetnoresoundingwinnerforbenefits.thisleadsustoconclude thatitstillearlydays. Themainroadblocktoimplementationappearstobethatitisdifficulttopresentabusiness case. Encouragingly,45%reportedthattheirBigDatainitiativeisorwillbeapartoftheirwiderdata managementinitiativessuchasmdm.morethanhalfofalltheorganizationshaveinfact implementeddatamanagementacrosstheboard(mdm,dataqualityanddatagovernance). 54%toldusthattheyalreadyhavedatagovernance. Managementunderstandingandawareness(42%),leadershipattheCxOlevel(18%)anda soundandwellqdocumentedbusinesscase(9%)areallcitedascriticaltosuccessful implementationofbigdatainitiatives.thissuggeststhereiscurrentlyalackofsufficientbuyin andcommitmentfromthebusinessside. BigDataisnotmainlyfocusedonanalyzingdatacollectedfromwebQbasedapplications. Customerdataisthemostsignificantdomainformostorganizationswithproductdatasecond andfinancialdatathird,bothafterunstructureddatawhichisclearlygainingininterest.so clearlyorganizationsarenotjustinterestedinanalyzingtwitterfeeds. 40%claimedthatitistheirintentiontouseHadooptechnologiesasthestagingareaforalltheir datainfuture(priortoloadingitintodatawarehousesorolapcubes),sothepossibleimpacton enterpriseetlstrategyneedstobeconsidered. Copyright 2013TheInformationDifferenceCompanyLtd.AllRightsReserved.

Hadoop & Big Data Market [Hardware, Software, Services, Hadoop-as-a- Service] - Trends, Geographical Analysis & Worldwide Market Forecasts (2012 2017)

Hadoop & Big Data Market [Hardware, Software, Services, Hadoop-as-a- Service] - Trends, Geographical Analysis & Worldwide Market Forecasts (2012 2017) Brochure More information from http://www.researchandmarkets.com/reports/2259062/ Hadoop & Big Data Market [Hardware, Software, Services, Hadoop-as-a- Service] - Trends, Geographical Analysis & Worldwide

More information

Global Hadoop Market (Hardware, Software, Services) applications, Geography, Haas, Global Trends,Opportunities, Segmentation and Forecast 2014-2021

Global Hadoop Market (Hardware, Software, Services) applications, Geography, Haas, Global Trends,Opportunities, Segmentation and Forecast 2014-2021 Brochure More information from http://www.researchandmarkets.com/reports/3050450/ Global Hadoop Market (Hardware, Software, Services) applications, Geography, Haas, Global Trends,Opportunities, Segmentation

More information

Big Data Vendor Revenue and Market Forecast 2012-2017

Big Data Vendor Revenue and Market Forecast 2012-2017 Big Data Vendor and Market Forecast 2012-2017 Contributing authors: Jeff Kelly, David Floyer, Dave Vellante, Stu Miniman Original publication date: February 19, 2013 The hype surrounding Big Data, which

More information

Global Big Data Enabled Market 2015-2019

Global Big Data Enabled Market 2015-2019 Brochure More information from http://www.researchandmarkets.com/reports/3498655/ Global Big Data Enabled Market 2015-2019 Description: Global Big Data Enabled Market 2015-2019 Covering: Market forecast

More information

TABLE OF CONTENTS 1 Chapter 1: Introduction 2 Chapter 2: Big Data Technology & Business Case 3 Chapter 3: Key Investment Sectors for Big Data

TABLE OF CONTENTS 1 Chapter 1: Introduction 2 Chapter 2: Big Data Technology & Business Case 3 Chapter 3: Key Investment Sectors for Big Data TABLE OF CONTENTS 1 Chapter 1: Introduction 1.1 Executive Summary 1.2 Topics Covered 1.3 Key Findings 1.4 Target Audience 1.5 Companies Mentioned 2 Chapter 2: Big Data Technology & Business Case 2.1 Defining

More information

TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON BIG DATA MULTI-PLATFORM JUNE 25-27, 2014 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY)

TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON BIG DATA MULTI-PLATFORM JUNE 25-27, 2014 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY) TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON BIG DATA MULTI-PLATFORM ANALYTICS JUNE 25-27, 2014 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY) info@technologytransfer.it www.technologytransfer.it

More information

Big Data Vendor Revenue and Market Forecast, 2011-2026

Big Data Vendor Revenue and Market Forecast, 2011-2026 Wikibon.com - http://wikibon.com Big Data Vendor Revenue and Market Forecast, 2011-2026 by Jeff Kelly - 31 March 2015 http://wikibon.com/big-data-vendor-revenue-and-market-forecast-2011-2026/ 1 / 13 Co-Authored

More information

TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON JUNE 3-4, 2015 JUNE 5, 2015 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY)

TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON JUNE 3-4, 2015 JUNE 5, 2015 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY) TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON Big Data and Analytics From Strategy to Implementation Data Virtualization in Practice JUNE 3-4, 2015 JUNE 5, 2015 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231

More information

Big Data Market Size and Vendor Revenues

Big Data Market Size and Vendor Revenues Analysis from The Wikibon Project February 2012 Big Data Market Size and Vendor Revenues Jeff Kelly, David Vellante, David Floyer A Wikibon Reprint The Big Data market is on the verge of a rapid growth

More information

Big Data Multi-Platform Analytics (Hadoop, NoSQL, Graph, Analytical Database)

Big Data Multi-Platform Analytics (Hadoop, NoSQL, Graph, Analytical Database) Multi-Platform Analytics (Hadoop, NoSQL, Graph, Analytical Database) Presented By: Mike Ferguson Intelligent Business Strategies Limited 2 Day Workshop : 25-26 September 2014 : 29-30 September 2014 www.unicom.co.uk/bigdata

More information

The Big Data Market 2014 2020: Opportunities, Challenges, Strategies, Industry Verticals and Forecasts

The Big Data Market 2014 2020: Opportunities, Challenges, Strategies, Industry Verticals and Forecasts Brochure More information from http://www.researchandmarkets.com/reports/2868472/ The Big Data Market 2014 2020: Opportunities, Challenges, Strategies, Industry Verticals and Forecasts Description: Big

More information

Mind Commerce. http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample

Mind Commerce. http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample Mind Commerce http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample Phone: 800.298.5699 (US) or +1.240.747.3093 or +1.240.747.3093 (Int'l) Hours: Monday - Thursday: 5:30am - 6:30pm

More information

Big Data and Telecom Analytics Market: Business Case, Market Analysis & Forecasts 2014-2019

Big Data and Telecom Analytics Market: Business Case, Market Analysis & Forecasts 2014-2019 MARKET RESEARCH STORE Big Data and Telecom Analytics Market: Business Case, Market Analysis & Forecasts 2014-2019 Market Research Store included latest deep and professional market research report on Big

More information

Big Data - Global Strategic Business Report

Big Data - Global Strategic Business Report Brochure More information from http://www.researchandmarkets.com/reports/2228010/ Big Data - Global Strategic Business Report Description: This report analyzes the Global market for Big Data in US$ Billion.

More information

Big Data and Telecom Analytics Market: Business Case, Market Analysis & Forecasts 2014-2019

Big Data and Telecom Analytics Market: Business Case, Market Analysis & Forecasts 2014-2019 Brochure More information from http://www.researchandmarkets.com/reports/2643647/ Big Data and Telecom Analytics Market: Business Case, Market Analysis & Forecasts 2014-2019 Description: Big Data refers

More information

Global Cloud Analytics Market 2015-2019

Global Cloud Analytics Market 2015-2019 Brochure More information from http://www.researchandmarkets.com/reports/3087451/ Global Cloud Analytics Market 2015-2019 Description: About Cloud Analytics Cloud analytics has emerged from the integration

More information

The Big Data Market: 2015 2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts

The Big Data Market: 2015 2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts The Big Data Market: 2015 2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts Phone: +44 20 8123 2220 Fax: +44 207 900 3970 office@marketpublishers.com The Big Data Market: 2015

More information

The Big Data Market: 2015-2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts

The Big Data Market: 2015-2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts Brochure More information from http://www.researchandmarkets.com/reports/3244020/ The Big Data Market: 2015-2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts Description: Big

More information

Brochure More information from http://www.researchandmarkets.com/reports/3065119/

Brochure More information from http://www.researchandmarkets.com/reports/3065119/ Brochure More information from http://www.researchandmarkets.com/reports/3065119/ Global Hadoop Market applications, Geography, Haas, Strategy, Industry Overview, Size, regional analysis, Share, Global

More information

The Big Data Market: Business Case, Market Analysis & Forecasts 2015-2020

The Big Data Market: Business Case, Market Analysis & Forecasts 2015-2020 Brochure More information from http://www.researchandmarkets.com/reports/2983902/ The Big Data Market: Business Case, Market Analysis & Forecasts 2015-2020 Description: Big Data refers to a massive volume

More information

Next Generation Data Analytics: Data as a Strategic Currency

Next Generation Data Analytics: Data as a Strategic Currency Next Generation Data Analytics: Data as a Strategic Currency July 2014 Joel P. Fishbein, Jr BMO Capital Markets Corp. joel.fishbein@bmo.com (212) 885-4159 Brett Fodero BMO Capital Markets Corp. brett.fodero@bmo.com

More information

Big Data. Lyle Ungar, University of Pennsylvania

Big Data. Lyle Ungar, University of Pennsylvania Big Data Big data will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus. McKinsey Data Scientist: The Sexiest Job of the 21st Century -

More information

CHANGES IN THE IT INDUSTRY IN THE PERIOD 2006-2012 WITH PARTICULAR EMPHASIS ON ANALYTICAL TOOLS TO SUPPORT MANAGEMENT OF LARGE CORPORATIONS

CHANGES IN THE IT INDUSTRY IN THE PERIOD 2006-2012 WITH PARTICULAR EMPHASIS ON ANALYTICAL TOOLS TO SUPPORT MANAGEMENT OF LARGE CORPORATIONS INFORMATION SYSTEMS IN MANAGEMENT Information Systems in Management (2013) Vol. 2 (1) 35 46 CHANGES IN THE IT INDUSTRY IN THE PERIOD 2006-2012 WITH PARTICULAR EMPHASIS ON ANALYTICAL TOOLS TO SUPPORT MANAGEMENT

More information

Synergic Partners: Spanish big-data pioneer

Synergic Partners: Spanish big-data pioneer Synergic Partners: Spanish big-data pioneer Analyst: Katy Ring 20 Mar, 2015 Synergic Partners offers a services portfolio around data engineering, big data and data science. The company focuses on business

More information

Global SME Big Data Market 2014-2018

Global SME Big Data Market 2014-2018 Brochure More information from http://www.researchandmarkets.com/reports/2873222/ Global SME Big Data Market 2014-2018 Description: About SME Big Data Big data solutions include a wide range of hardware,

More information

The Big Data Market: Business Case, Market Analysis & Forecasts 2015-2020

The Big Data Market: Business Case, Market Analysis & Forecasts 2015-2020 The Big Data Market: Business Case, Market Analysis & Forecasts 2015-2020 Phone: +44 20 8123 2220 Fax: +44 207 900 3970 office@marketpublishers.com The Big Data Market: Business Case, Market Analysis &

More information

TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON JUNE 6-7, 2016 JUNE 8-9, 2016 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY)

TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON JUNE 6-7, 2016 JUNE 8-9, 2016 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY) TECHNOLOGY TRANSFER PRESENTS MIKE FERGUSON Big Data and Analytics From Strategy to Implementation Enterprise Data Governance & Master Data Management JUNE 6-7, 2016 JUNE 8-9, 2016 RESIDENZA DI RIPETTA

More information

RESEARCH NOTE TECHNOLOGY VALUE MATRIX SECOND HALF 2012 ANALYTICS THE BOTTOM LINE MARKET OVERVIEW. October 2012. Document M144

RESEARCH NOTE TECHNOLOGY VALUE MATRIX SECOND HALF 2012 ANALYTICS THE BOTTOM LINE MARKET OVERVIEW. October 2012. Document M144 RESEARCH NOTE TECHNOLOGY VALUE MATRIX SECOND HALF 2012 ANALYTICS THE BOTTOM LINE The future of analytics resides in end user data access and analysis. Over the past six months, companies have demanded

More information

Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2014-2019

Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2014-2019 Brochure More information from http://www.researchandmarkets.com/reports/3006484/ Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2014-2019 Description: Big Data and predictive

More information

BMC Software's batch-job juggernaut gets hip with Hadoop support

BMC Software's batch-job juggernaut gets hip with Hadoop support BMC Software's batch-job juggernaut gets hip with Hadoop support Analyst: Michael Coté 7 Nov, 2013 The domain of managing scheduled execution of arbitrary workloads batch-job management can seem like a

More information

BIG DATA ANALYTICS. Vishy Venugopalan

BIG DATA ANALYTICS. Vishy Venugopalan + BIG DATA ANALYTICS Vishy Venugopalan + AGENDA n Introduction: The Age of Big Data n The Analytics Adoption Curve n The New Data Stack n Opportunities in the Big Data Analytics Market n Investment Candidates

More information

CPS 516: Data-intensive Computing Systems. Instructor: Shivnath Babu TA: Zilong (Eric) Tan

CPS 516: Data-intensive Computing Systems. Instructor: Shivnath Babu TA: Zilong (Eric) Tan CPS 516: Data-intensive Computing Systems Instructor: Shivnath Babu TA: Zilong (Eric) Tan The World of Big Data ebay had 6.5 PB of user data + 50 TB/day in 2009 From http://www.umiacs.umd.edu/~jimmylin/

More information

Hadoop Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2012 2018

Hadoop Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2012 2018 Transparency Market Research Hadoop Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2012 2018 Buy Now Request Sample Published Date: July 2013 Single User License: US $ 4595

More information

Zementis. Universal Deployment of KNIME Models. Big Data and Real-time Scoring. KNIME User Group Meeting, Berlin February

Zementis. Universal Deployment of KNIME Models. Big Data and Real-time Scoring. KNIME User Group Meeting, Berlin February Zementis Universal Deployment of KNIME Models Big Data and Real-time Scoring KNIME User Group Meeting, Berlin February 2015 www.zementis.com Zementis Zementis Zementis provides software for operational

More information

TOP 8 TRENDS FOR 2016 BIG DATA

TOP 8 TRENDS FOR 2016 BIG DATA The year 2015 was an important one in the world of big data. What used to be hype became the norm as more businesses realized that data, in all forms and sizes, is critical to making the best possible

More information

Big Data in Financial Services Industry: Market Analysis and Forecasts 2015-2020

Big Data in Financial Services Industry: Market Analysis and Forecasts 2015-2020 Brochure More information from http://www.researchandmarkets.com/reports/3517525/ Big Data in Financial Services Industry: Market Analysis and Forecasts 2015-2020 Description: Financial Services (credit

More information

Market for Telecom Structured Data, Big Data, and Analytics: Business Case, Analysis and Forecasts 2015-2020

Market for Telecom Structured Data, Big Data, and Analytics: Business Case, Analysis and Forecasts 2015-2020 Brochure More information from http://www.researchandmarkets.com/reports/3128462/ Market for Telecom Structured Data, Big Data, and Analytics: Business Case, Analysis and Forecasts 2015-2020 Description:

More information

Big Data reconsidered Separating Hype from Reality for Hosting and Cloud Providers

Big Data reconsidered Separating Hype from Reality for Hosting and Cloud Providers Big Data reconsidered Separating Hype from Reality for Hosting and Cloud Providers Matthew Aslett Research Director, Data Management and Analytics, 451 Research Matthew Aslett Research Director, Data Management

More information

Fisher College of Business The Ohio State University. Syllabus

Fisher College of Business The Ohio State University. Syllabus Fisher College of Business The Ohio State University Syllabus Business Adm 3630.05 Introduction to Business Analytics (2 Credit Hours) Fall Semester 2013 Instructor: Ralph Greco, BS. MS. Industrial Engineering

More information

Taming the Beast of Big Data

Taming the Beast of Big Data Taming the Beast of Big Data Jeff Zakrzewski Vice President Sogeti USA Local Touch, Global Reach 1 Agenda What is Big Data? Some Sources of Big Data Approaches to Big Data The Hadoop Buzz Vertical Perspective

More information

BITKOM& NIK - Big Data Wo liegen die Chancen für den Mittelstand?

BITKOM& NIK - Big Data Wo liegen die Chancen für den Mittelstand? BITKOM& NIK - Big Data Wo liegen die Chancen für den Mittelstand? The Big Data Buzz big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database

More information

September 2014 INSIGHTS. Infrastructure in 2014: Past, Present, & Future. Scott Card, Partner Zack Lesko, CTO Nick Wetegrove, Analyst

September 2014 INSIGHTS. Infrastructure in 2014: Past, Present, & Future. Scott Card, Partner Zack Lesko, CTO Nick Wetegrove, Analyst September 2014 INSIGHTS Infrastructure in 2014: Past, Present, & Future Scott Card, Partner Zack Lesko, CTO Nick Wetegrove, Analyst The Traditional Emergence Data of vs. Big Big Data Data Summary SIZE:

More information

F E B R U A R Y 2 0 1 6. Business Intelligence and Analytics Platforms Market Map. Shea & Company, LLC

F E B R U A R Y 2 0 1 6. Business Intelligence and Analytics Platforms Market Map. Shea & Company, LLC F E B R U A R Y 2 0 1 6 Business Intelligence and Analytics Platforms Market Map Shea & Company, LLC Agenda Outlook & Key Themes Business Intelligence & Analytics Technology Stack and Landscape Transaction

More information

Big Data Success Stories

Big Data Success Stories Big Data Success Stories Dr. Vincenzo Chiochia European TDWI Conference Munich, Germany June 22-24, 2015 Understanding Big Data A majority of organizations carry out business based on insights gained from

More information

Big Data and Advanced Analytics Technologies and Use Cases"

Big Data and Advanced Analytics Technologies and Use Cases Big Data and Advanced Analytics Technologies and Use Cases" Colin White President, BI Research DAMA Portland February 2013" Agenda There is considerable interest at present on the topic of big data. Much

More information

What s New in CA ERwin Modeling r9.6?

What s New in CA ERwin Modeling r9.6? What s New in CA ERwin Modeling r9.6? A First Look C. Neil Buchwalter CA Technologies March 18, 2015 ER01 Session Abstract Presentation, collaboration and governance are just a few of the buzzwords we

More information

Big Data Technologies Compared June 2014

Big Data Technologies Compared June 2014 Big Data Technologies Compared June 2014 Agenda What is Big Data Big Data Technology Comparison Summary Other Big Data Technologies Questions 2 What is Big Data by Example The SKA Telescope is a new development

More information

Big Data Services Market in Western Europe 2015-2019

Big Data Services Market in Western Europe 2015-2019 Brochure More information from http://www.researchandmarkets.com/reports/3301866/ Big Data Services Market in Western Europe 2015-2019 Description: About Big Data Services Data generated from various sources

More information

Software and the IoT: Platforms, data, and analytics

Software and the IoT: Platforms, data, and analytics Internet of Things - Volume 2 Software and the IoT: Platforms, data, and analytics The role of software across the enterprise and consumer IoT Equity Research The Internet of Things takes shape as the

More information

February 2, 2012 The Forrester Wave : Enterprise Hadoop Solutions, Q1 2012 by James G. Kobielus for Application Development & Delivery Professionals

February 2, 2012 The Forrester Wave : Enterprise Hadoop Solutions, Q1 2012 by James G. Kobielus for Application Development & Delivery Professionals February 2, 2012 The Forrester Wave : Enterprise Hadoop Solutions, Q1 2012 by James G. Kobielus for Application Development & Delivery Professionals Making Leaders Successful Every Day Wave February 2,

More information

David M. Kroenke and David J. Auer Database Processing 11 th Edition Fundamentals, Design, and Implementation. Chapter Objectives

David M. Kroenke and David J. Auer Database Processing 11 th Edition Fundamentals, Design, and Implementation. Chapter Objectives David M. Kroenke and David J. Auer Database Processing 11 th Edition Fundamentals, Design, and Implementation Chapter One: Introduction 1-1 Chapter Objectives To understand the nature and characteristics

More information

Mind Commerce. http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample

Mind Commerce. http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample Mind Commerce http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample Phone: 800.298.5699 (US) or +1.240.747.3093 or +1.240.747.3093 (Int'l) Hours: Monday - Thursday: 5:30am - 6:30pm

More information

Copyright 2013 wolfssl Inc. All rights reserved. 2

Copyright 2013 wolfssl Inc. All rights reserved. 2 - - Copyright 2013 wolfssl Inc. All rights reserved. 2 Copyright 2013 wolfssl Inc. All rights reserved. 2 Copyright 2013 wolfssl Inc. All rights reserved. 3 Copyright 2013 wolfssl Inc. All rights reserved.

More information

Modeling Big Data Systems by Extending the Palladio Component Model

Modeling Big Data Systems by Extending the Palladio Component Model München, 2015-11-06 Modeling Big Data Systems by Extending the Palladio Component Model 6 th Symposium on Software Performance (SSP) 2015 Johannes Kroß 1, Andreas Brunnert 1, Helmut Krcmar 2 1 fortiss

More information

VIEWPOINT. High Performance Analytics. Industry Context and Trends

VIEWPOINT. High Performance Analytics. Industry Context and Trends VIEWPOINT High Performance Analytics Industry Context and Trends In the digital age of social media and connected devices, enterprises have a plethora of data that they can mine, to discover hidden correlations

More information

Intro to BI. Mul0- dimensional Analysis

Intro to BI. Mul0- dimensional Analysis Intro to BI BI Vendor Landscape BI Roles & Responsibili0es Data Governance and Quality DW Architectures ETL Processes BI Capabili0es & Maturity Mul0- dimensional Analysis BI Vendors and Products Module

More information

Fisher College of Business The Ohio State University. Syllabus

Fisher College of Business The Ohio State University. Syllabus Fisher College of Business The Ohio State University Syllabus Business Adm 3630.05 Introduction to Business Analytics (2 Credit Hours) Autumn Semester 2015 Instructor: Ralph, BS. MS. Industrial Engineering

More information

Hadoop - Global Strategic Business Report

Hadoop - Global Strategic Business Report Brochure More information from http://www.researchandmarkets.com/reports/3301141/ Hadoop - Global Strategic Business Report Description: This report analyzes the worldwide markets for Hadoop in US$ Million

More information

Big Data Support Services. Service Definition

Big Data Support Services. Service Definition 1 3 Big Data Support Services Service Definition BIG DATA SUPPORT SERVICES Service Description The Big Data Support Services are part of the Cognizant Information Management service family. Providing a

More information

Are Small Consultancies Best for Big Data Projects?

Are Small Consultancies Best for Big Data Projects? Are Small Consultancies Best for Big Data Projects? Big data is attracting the attention of all types of buy-side organizations. But because the technologies involved are immature and there is a lack of

More information

Stream Processing on Demand for Lambda Architectures

Stream Processing on Demand for Lambda Architectures Madrid, 2015-09-01 Stream Processing on Demand for Lambda Architectures European Workshop on Performance Engineering (EPEW) 2015 Johannes Kroß 1, Andreas Brunnert 1, Christian Prehofer 1, Thomas A. Runkler

More information

Connecting the Dots. The Progress DataDirect Vision & Roadmap. Brad Wright Product Management October 7, 2013

Connecting the Dots. The Progress DataDirect Vision & Roadmap. Brad Wright Product Management October 7, 2013 Connecting the Dots The Progress DataDirect Vision & Roadmap Brad Wright Product Management October 7, 2013 Safe Harbor This roadmap is for informational purposes only, and the reader is hereby cautioned

More information

Taming the Beast of Big Data

Taming the Beast of Big Data Taming the Beast of Big Data Jeff Zakrzewski Vice President Sogeti USA Local Touch, Global Reach 1 Agenda What is Big Data? Some Sources of Big Data Approaches to Big Data The Hadoop Buzz Vertical Perspective

More information

TECHNOLOGY TRANSFER PRESENTS OCTOBER 16 2012 OCTOBER 17 2012 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY)

TECHNOLOGY TRANSFER PRESENTS OCTOBER 16 2012 OCTOBER 17 2012 RESIDENZA DI RIPETTA - VIA DI RIPETTA, 231 ROME (ITALY) TECHNOLOGY TRANSFER PRESENTS RICK VAN DER LANS Data Virtualization for Agile Business Intelligence Systems New Database Technology for Data Warehousing OCTOBER 16 2012 OCTOBER 17 2012 RESIDENZA DI RIPETTA

More information

Big Data for Architects

Big Data for Architects Big Data for Architects Sam Babad @ MidLink sam@midlink.ca 052-595-8885 Agenda What is BigData BigData challenges Textbook big data architecture Analysis, visualization & self service BigData in the cloud

More information

Expand Your Digital Horizon With Big Data by Brian Hopkins and Boris Evelson for CIOs

Expand Your Digital Horizon With Big Data by Brian Hopkins and Boris Evelson for CIOs September 30, 2011 Expand Your Digital Horizon With Big Data by Brian Hopkins and Boris Evelson for CIOs Making Leaders Successful Every Day September 30, 2011 Expand Your Digital Horizon With Big Data

More information

AbInitio. Acorn System. Active Strategy. Actuate 1) 2) Adeptia. Adress Solutions. Aero Text. Aleri. Anderson Analytics. Angoss. Antares.

AbInitio. Acorn System. Active Strategy. Actuate 1) 2) Adeptia. Adress Solutions. Aero Text. Aleri. Anderson Analytics. Angoss. Antares. Klassifizierung wichtiger Anbieter für Business Intelligence und Datenmanagement Quelle: CPM-Kompendium, Wolfgang Martin Team/CSA Consulting (www.wolfgang-martin-team.net) AbInitio Acorn System Active

More information

Tips and Techniques on how to better Monitor, Manage and Optimize your MicroStrategy System High ROI DW and BI Solutions

Tips and Techniques on how to better Monitor, Manage and Optimize your MicroStrategy System High ROI DW and BI Solutions Tips and Techniques on how to better Monitor, Manage and Optimize your MicroStrategy System InfoCepts 'LJLWDOO\ VLJQHG E\,QIR&HSWV '1 FQ,QIR&HSWV JQ,QIR&HSWV F 8QLWHG 6WDWHV O 86 R,QIR&HSWV RX,QIR&HSWV

More information

Questionnaire about the skills necessary for people. working with Big Data in the Statistical Organisations

Questionnaire about the skills necessary for people. working with Big Data in the Statistical Organisations Questionnaire about the skills necessary for people working with Big Data in the Statistical Organisations Preliminary results of the survey (19.08 2014) More detailed analysis will be prepared by October

More information

David M. Kroenke and David J. Auer Database Processing 12 th Edition

David M. Kroenke and David J. Auer Database Processing 12 th Edition David M. Kroenke and David J. Auer Database Processing 12 th Edition Fundamentals, Design, and Implementation ti Chapter One: Introduction Modified & translated by Walter Chen Dept. of Civil Engineering

More information

NoSQL'Road'Show,'Basel'

NoSQL'Road'Show,'Basel' Photo'credit:'Wilson'Loo'on'Flickr'h>p://bit.ly/Pf43nE' NoSQL,'NewSQL,'Big'Data 'Total'Data' The'Future'of'Enterprise'Data'Management'' Ma>hew'Asle>' Research'Manager,'Data'Management'and'AnalyDcs' NoSQL'Road'Show,'Basel'

More information

Supported Platforms. HP Vertica Analytic Database. Software Version: 7.0.x

Supported Platforms. HP Vertica Analytic Database. Software Version: 7.0.x HP Vertica Analytic Database Software Version: 7.0.x Document Release Date: 5/7/2014 Legal Notices Warranty The only warranties for HP products and services are set forth in the express warranty statements

More information

Analytics framework: creating the data-centric organisation to optimise business performance

Analytics framework: creating the data-centric organisation to optimise business performance Research Report Analytics framework: creating the data-centric organisation to optimise business performance October 2013 Justin van der Lande 2 Contents [1] Slide no. 5. Executive summary 6. Executive

More information

Teradata The Leader in Enterprise Data Warehousing

Teradata The Leader in Enterprise Data Warehousing Teradata The Leader in Enterprise Data Warehousing June 2008 Note to Investors Certain non-gaap financial information regarding operating results may be discussed during this presentation. Reconciliations

More information

Contents. Pentaho Corporation. Version 5.1. Copyright Page. New Features in Pentaho Data Integration 5.1. PDI Version 5.1 Minor Functionality Changes

Contents. Pentaho Corporation. Version 5.1. Copyright Page. New Features in Pentaho Data Integration 5.1. PDI Version 5.1 Minor Functionality Changes Contents Pentaho Corporation Version 5.1 Copyright Page New Features in Pentaho Data Integration 5.1 PDI Version 5.1 Minor Functionality Changes Legal Notices https://help.pentaho.com/template:pentaho/controls/pdftocfooter

More information

Global Social Business Intelligence (BI) Market 2015-2019

Global Social Business Intelligence (BI) Market 2015-2019 Brochure More information from http://www.researchandmarkets.com/reports/3093594/ Global Social Business Intelligence (BI) Market 2015-2019 Description: About Social Business Intelligence Social media

More information

Il mondo dei DB Cambia : Tecnologie e opportunita`

Il mondo dei DB Cambia : Tecnologie e opportunita` Il mondo dei DB Cambia : Tecnologie e opportunita` Giorgio Raico Pre-Sales Consultant Hewlett-Packard Italiana 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject

More information

(1) Required: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, Kimball 2013 ISBN-13: 978-1118530801

(1) Required: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, Kimball 2013 ISBN-13: 978-1118530801 DESIGNING AND IMPLEMENTING A DATA WAREHOUSE INSTRUCTOR: STANISLAV SELTSER, STANISLAV.SELTSER@BU.EDU MET CS 689 Data Warehousing 1. Course Designator/Course Number 2. Course Title Designing and implementing

More information

TECHNOLOGY VALUE MATRIX SECOND HALF 2014 ANALYTICS

TECHNOLOGY VALUE MATRIX SECOND HALF 2014 ANALYTICS RESEARCH NOTE November 2014 TECHNOLOGY VALUE MATRIX SECOND HALF 2014 ANALYTICS THE BOTTOM LINE The analytics market has evolved from a small market of large, established vendors with predominantly on-premise

More information

Understanding How Sensage Compares/Contrasts with Hadoop

Understanding How Sensage Compares/Contrasts with Hadoop Frequently Asked Questions Understanding How Sensage Compares/Contrasts with Hadoop 1. How does Sensage s approach to managing large, distributed data systems compare/contrast with Hadoop in terms of storage,

More information

! PRIVATE!PAGES! DRUPAL!7!WEB!CONTENT!MANAGEMENT!

! PRIVATE!PAGES! DRUPAL!7!WEB!CONTENT!MANAGEMENT! UNIVERSITY*OF*CALGARY InformationTechnologies PRIVATEPAGES DRUPAL7WEBCONTENTMANAGEMENT September2015 TableofContents FirstSteps...1 AddingaPrivatePage...2 AccessControl...4 PrivatePages Drupal7WebContentManagement

More information

Bringing Cool into Your BI Portfolio Twitter: #coolbi. TDWI, November 2012 Cindi Howson Founder, BI Scorecard Contact: cindihowson@biscorecard.

Bringing Cool into Your BI Portfolio Twitter: #coolbi. TDWI, November 2012 Cindi Howson Founder, BI Scorecard Contact: cindihowson@biscorecard. Bringing Cool into Your BI Portfolio Twitter: #coolbi TDWI, November 2012 Cindi Howson Founder, BI Scorecard Contact: cindihowson@biscorecard.com 1 Biography Founder of BI Scorecard, with 20 years experience

More information

Data Doesn t Communicate Itself Using Visualization to Tell Better Stories

Data Doesn t Communicate Itself Using Visualization to Tell Better Stories SAP Brief Analytics SAP Lumira Objectives Data Doesn t Communicate Itself Using Visualization to Tell Better Stories Tap into your data big and small Tap into your data big and small In today s fast-paced

More information

W o r l d w i d e B u s i n e s s A n a l y t i c s S o f t w a r e 2 0 1 3 2 0 1 7 F o r e c a s t a n d 2 0 1 2 V e n d o r S h a r e s

W o r l d w i d e B u s i n e s s A n a l y t i c s S o f t w a r e 2 0 1 3 2 0 1 7 F o r e c a s t a n d 2 0 1 2 V e n d o r S h a r e s Global Headquarters: 5 Speen Street Framingham, MA 01701 USA P.508.872.8200 F.508.935.4015 www.idc.com M A R K E T A N A L Y S I S W o r l d w i d e B u s i n e s s A n a l y t i c s S o f t w a r e 2

More information

WHITE PAPER. Data Migration and Access in a Cloud Computing Environment INTELLIGENT BUSINESS STRATEGIES

WHITE PAPER. Data Migration and Access in a Cloud Computing Environment INTELLIGENT BUSINESS STRATEGIES INTELLIGENT BUSINESS STRATEGIES WHITE PAPER Data Migration and Access in a Cloud Computing Environment By Mike Ferguson Intelligent Business Strategies March 2014 Prepared for: Table of Contents Introduction...

More information

Hadoop Market - Global Industry Analysis, Size, Share, Growth, Trends, And Forecast, 2012-2018

Hadoop Market - Global Industry Analysis, Size, Share, Growth, Trends, And Forecast, 2012-2018 Brochure More information from http://www.researchandmarkets.com/reports/2622818/ Hadoop Market - Global Industry Analysis, Size, Share, Growth, Trends, And Forecast, 2012-2018 Description: An exponential

More information

Balancing Opportunity and Risk in Big Data

Balancing Opportunity and Risk in Big Data Balancing Opportunity and Risk in Big Data A Survey of Enterprise Priorities and Strategies for Harnessing Big Data WHITE PAPER This document contains Confidential, Proprietary and Trade Secret Information

More information

Threat!and!Vulnerability!Assessments!

Threat!and!Vulnerability!Assessments! ThreatandVulnerabilityAssessments https://www.cybersecdefense.com @cybersecdefense 13720JetportCommerceParkway STE13 Ft.Myers,FL33913 COPYRIGHT 2015,CybersecurityDefenseSolutions,LLC ALLRIGHTSRESERVED

More information

Business Intelligence. Advanced visualization. Reporting & dashboards. Mobile BI. Packaged BI

Business Intelligence. Advanced visualization. Reporting & dashboards. Mobile BI. Packaged BI Data & Analytics 1 Data & Analytics Solutions - Overview Information Management Business Intelligence Advanced Analytics Data governance Data modeling & architecture Master data management Enterprise data

More information

Global Big Data Market in the Oil and Gas Sector 2014-2018

Global Big Data Market in the Oil and Gas Sector 2014-2018 Brochure More information from http://www.researchandmarkets.com/reports/3042448/ Global Big Data Market in the Oil and Gas Sector 2014-2018 Description: About Global Big Data Big data solutions are a

More information

Benchmark Report. Hadoop in the Enterprise With Maturity Come Manageability Challenges

Benchmark Report. Hadoop in the Enterprise With Maturity Come Manageability Challenges Benchmark Report Hadoop in the Enterprise With Maturity Come Manageability Challenges By Wayne Eckerson Principal Consultant Eckerson Group April 2014 Table of Contents Executive Summary... 3 Methodology...

More information

Protecting Data in a Spooky world Data Masking Technologies DAMA RMC Oct. 29, 2014

Protecting Data in a Spooky world Data Masking Technologies DAMA RMC Oct. 29, 2014 Business Glossary Business Intelligence Data Architecture Master Data Management Protecting Data in a Spooky world Data Masking Technologies DAMA RMC Oct. 29, 2014 Aspen Information Solutions, Inc Lowell

More information

SAP HANA, HADOOP and other Big Data Tools

SAP HANA, HADOOP and other Big Data Tools SAP HANA, HADOOP and other Big Data Tools Big Data: Why now? x2 90% digital data globally doubles every two years 1 of all data is unstructured and cannot be handled with traditional analytics tools 1

More information

APPLICATION PLATFORMS AND BUSINESS PROCESSES

APPLICATION PLATFORMS AND BUSINESS PROCESSES APPLICATION PLATFORMS AND BUSINESS PROCESSES Sponsored by Microsoft Corporation Copyright 2012 Chappell & Associates Whether it s a large enterprise, a small company, or a government agency, every organization

More information

A Tour of the Zoo the Hadoop Ecosystem Prafulla Wani

A Tour of the Zoo the Hadoop Ecosystem Prafulla Wani A Tour of the Zoo the Hadoop Ecosystem Prafulla Wani Technical Architect - Big Data Syntel Agenda Welcome to the Zoo! Evolution Timeline Traditional BI/DW Architecture Where Hadoop Fits In 2 Welcome to

More information

Hemant Kulkarni MOBILE BI HYPE OR REAL NEED?

Hemant Kulkarni MOBILE BI HYPE OR REAL NEED? Hemant Kulkarni MOBILE BI HYPE OR REAL NEED? AGENDA WHY PEOPLE STILL FILL ITS HYPE? WHAT GARTNER HYPE CYCLE FOR EMERGING TRENDS SAYS? WHAT IS THE REALITY? MOBILE BI EVOLUTION MOBILE BI IS NOT JUST BI ON

More information

Market Overview: Big Data Integration

Market Overview: Big Data Integration For: Enterprise Architecture Professionals Market Overview: Big Data Integration by Noel Yuhanna, December 5, 2014 Key Takeaways Big Data Creates New Data Challenges Today, most big data deployments are

More information

Supported Platforms. HP Vertica Analytic Database. Software Version: 7.1.x

Supported Platforms. HP Vertica Analytic Database. Software Version: 7.1.x HP Vertica Analytic Database Software Version: 7.1.x Document Release Date: 10/14/2015 Legal Notices Warranty The only warranties for HP products and services are set forth in the express warranty statements

More information

Big Data Analytics in Facilities Management

Big Data Analytics in Facilities Management Big Data Analytics in Facilities Management Data Can Drive Performance Behind-the-scenes 9A68-67 May 2015 Contents Section Slide Number Executive Summary 3 Methodology 5 BDA Fundamentals 7 FM and BDA 12

More information

The Challenge of Big Data Benchmarking Large-Scale Data Management Insights from Benchmark Research

The Challenge of Big Data Benchmarking Large-Scale Data Management Insights from Benchmark Research Benchmarking Large-Scale Data Management Insights from Presentation Confidentiality Statement The materials in this presentation are protected under the confidential agreement and/or are copyrighted materials

More information