《管理學(xué)專業(yè)英語教程（第四版下）》課件Unit 6 Big Data-The Managment Revolution

Outlines123IntroductionDimensionsofBigDataFiveManagementChallengesIntroductionWedefine‘BigData’asacapabilitythatallowscompaniestoextractvaluefromlargevolumesofdata,Likeanycapability,itrequiresinvestmentintechnologies,processesandgovernance.

ValueVarietyreferstothenumberofdatatypes.Technologicaladvancesalloworganizationstogeneratevarioustypesofstructured,semi-structured,andunstructureddata.Velocityreferstothespeedatwhichdataaregeneratedandprocessed.Volumereferstotheamountofdataanorganizationoranindividualcollectsand/orgenerates.DimensionsofBigDataWhatarethekeydifferencebetween“BigDataand“analytics”?BigData≠analyticsSASaddedtwoadditionaldimensionstobigdata:variabilityandcomplexity.Variabilityreferstothevariationindataflowrates.Complexityreferstothenumberofdatasources.Oracleintroducedvalueasanadditionaldimensionofbigdata.Firmsneedtounderstandtheimportanceofusingbigdatatoincreaserevenue,andconsidertheinvestmentcostofabigdataproject.AdditionalDimensionsofBigDataBigData≠analyticsIBMaddedveracityasafourthdimension,whichrepresentstheunreliabilityanduncertaintylatentindatasources.AnintegratedviewofBigDataThethreeedgesoftheintegratedviewofbigdatarepresentthreedimensionsofbigdata:volume,velocity,andvariety.Insidethetrianglearethefivedimensionsofbigdatathatareaffectedbythegrowthofthethreetriangulardimensions:veractiy,variability,complexity,decay,andvalue.Thegrowthofthethree-edgeddimensionsisnegativelyrelatedtoveracity,butposibitvelyrelatedtocomplexity,variability,decay,andvalue.Thethreeedgesoftheintegratedviewofbigdatarepresentthreedimensionsofbigdata:volume,velocity,andvariety.Insidethetrianglearethefivedimensionsofbigdatathatareaffectedbythegrowthofthethreetriangulardimensions:veracity,variability,complexity,decay,andvalue.Thegrowthofthethree-edgeddimensionsisnegativelyrelatedtoveracity,butpositivelyrelatedtocomplexity,variability,decay,andvalue.ImpactsofBigDataApplicationPersonalizationmarketingByexploitingbigdatafrommultiplesources,firmscandeliverpersonalizedproduct/servicerecommendations,coupons,andotherpromotionaloffers.BetterPricingHarnessingbigdatacollectedfromcustomerinteractionsallowsfirmstopriceappropriatelyandreaptherewards.CostReductionBigdataanalyticsleadstobetterdemandforecasts,moreefficientroutingwithvisualizationandreal-timetrackingduringshipments,andhighlyoptimizeddistributionnetworkmanagement.ImprovedcustomerserviceBigdataanalyticscanintegratedatafrommultiplecommunicationchannels(e.g.phone,email,instantmessage)andassistcustomerservicepersonnelinunderstandingthecontextofcustomerproblemsholisticallyandaddressingproblemsquickly.FiveManagementChallengesLeadershipTalentManagementTechnologyConcernsDecisionMakingCompanyCultureBigdata’spowerdoesnoterasetheneedforvisionorhumaninsight.Asdatabecomecheaper,thecomplementstodatabecomemorevaluable.NewtechnologiesdorequireaskillsetthatisalientomostITdepartments.It’stooeasytomistakecorrelationforcausationandtofindmisleadingpatternsinthedata.BigDataTechnologyConcerns-BigDataSecurityChallengesTheFutureofBigDataBigdata'semergencehasnotremainedisolatedtoafewsectorsorspheresoftechnology,insteaddemonstratingbroadapplicationsacrossindustries.Inlightofthisreality,companiesmustfirstpursuebigdatacapabilitiesasnecessaryground-leveldevelopments,whichinturnmayfacilitatecompetitiveadvantages.Formidablechallengesfacefirmsinpursuitofbigdataintegration,butthepotentialbenefitsofbigdatapromisetopositivelyimpactcompanyoperations,marketing,customerexperience,andmore.Text2:IsYourCompanyReadyforaDigitalFuture?-OutlineBigDataFrameworkFourBigDataStrategiesFourPathwaysforTransformationTheEvolutionofBigData1234BigDataFrameworkSocialAnalyticsDecisionSciencePerformanceManagementDataExplorationDataTypeNon-transactionalDataTransactionalDataMeasurementExperimentationBusinessObjectiveBigDataFrameworkTheFirstdimension-BusinessObjectiveWhendevelopingbigdatacapabilities,companiestrytomeasureorexperiment.Whenmeasuring,organizationsknowexactlywhattheyarelookingforandlooktoseewhatthevaluesofthemeasuresare.Whentheobjectiveistoexperiment,companiestreatquestionsasahypothesisandusescientificmethodstoverifythem.TheSeconddimension-DataTypeIntheirnormalcourseoffunctioning,companiescollectdataontheiroperationsandcaptureitintheirdatabasethathasastructureorschema.Wecallthistransactionaldata.Inotherinstances,companiesdealwithdatathatcomefromsourcesotherthantransactionsandaretypicallyunstructured(e.g.,socialmediadata).PopularBigDataTechniques(1)TransactionalDataBusinessIntelligence/OnlineAnalyticalProcessing(OLAP):?Usersinteractivelyanalyzemultidimensionaldata

?Userscanroll-up,drill-down,andslicedata

?BItoolsprovidedashboardandreportcapabilitiesClusterAnalysis:segmentobjectsintogroupsbasedonsimilarpropertiesorattributesDataMining:ProcesstodiscoverandextractnewpatternsinlargedatasetsPredictiveModeling:Amodeliscreatedtobestpredicttheprobabilityofanoutcome.A/BTesting:AmethodoftestinginwhichacontrolgroupiscomparedtotestgroupstodetermineifthereisanimprovementbasedonthetestconditionTechniquePopularBigDataTechniques(2)Non-transactionalDataCrowdsourcing:?Aprocessforcollectingdatafromalargecommunityordistributedgroupofpeople

?IdeasubmissionisacommoncrowdsourcingactivityTextualAnalysis:?Computeralgorithmsthatanalyzenaturallanguage

?TopicscanbeextractedfromtextalongwiththeirlinkagesSentimentAnalysis:?Aformoftextualanalysisthatdeterminesapositive,negativeorneutralreaction?OftenusedinmarketingbrandcampaignsNetworkAnalysis:?Amethodologytoanalyzetherelationshipamongnodes(e.g.,people)

?Onsocialmediaplatforms,itcanbeusedtocreatethesocialgraphoffollowerandfriends’connectionsamongusersTechniqueFourBigDataStrategiesPerformanceManagementByexploitingbigdatafrommultiplesources,firmscandeliverpersonalizedproduct/servicerecommendations,coupons,andotherpromotionaloffers.DataExplorationHarnessingbigdatacollectedfromcustomerinteractionsallowsfirmstopriceappropriatelyandreaptherewards.SocialAnalyticsBigdataanalyticsleadstobetterdemandforecasts,moreefficientroutingwithvisualizationandreal-timetrackingduringshipments,andhighlyoptimizeddistributionnetworkmanagement.DecisionScienceBigdataanalyticscanintegratedatafrommultiplecommunicationchannels(e.g.phone,email,instantmessage)andassistcustomerservicepersonnelinunderstandingthecontextofcustomerproblemsholisticallyandaddressingproblemsquickly.Howcompaniescompareondigitalbusinesstransformation?FourPathwaysforTransformationStandardizefirstMovecompaniesfromtheSilosandComplexityquadranttotheindustrializedquadrant.RelyonbuildingaplatformmindsetwithAPI-enabledservices.ImprovecustomerexperiencefirstMovefromtheSilosandComplexitytotheIntegratedExperiencequadrant.Developnewattractiveoffers,buildmobileappsandwebsites,improvecallcenters,andempowerrelationshipmanagers.TakestairstepsAlternatetheirfocusfromimprovingcustomerexperiencetoimprovingoperationsandthenbackagain.Createaneworganization.Allowanenterprisetobuilditscustomerbase,people,culture,processes,andsystemsfromscratchtobefuture-ready.BigData2.0(2005-2014)Bigdata2.0isdrivenbyWeb2.0andthesocialmediaphenomenon.Web2.0referstoawebparadigmthatevolvedfromthewebtechnologiesofthe1990sandallowedwebuserstointeractwithwebsitesandcontributetheirowncontenttothewebsites.BigData1.0(1994-2004)Bigdata1.0coincideswiththeadventofe-commercein1994,duringwhichtimeonlinefirmswerethemaincontributorsthewebcontent.User-generatedcontentwasonlyamarginalpartofwebcontentduetot