6 Top Business Benefits of Real-Time Data Analytics

That's a great use case for real-time data. 3. Quickly detect and address operational issues. Squads started in the tech industry but have ... TechAccelerator Whatisdatascience?Theultimateguide ViewMore Sharethisitemwithyournetwork: By DonaldFarmer, TreeHiveStrategy Published:11Jan2021 Consultingwithclientsafewyearsago,Iwouldhaveplacedquiteanemphasisontheneedtodistinguishbetweenreal-timedataandright-timedata.Ifyourbusinessprocessescouldbeservedwithhourlyupdates,whydeployexpensivereal-timeanalyticstoolstodeliverthemeveryfewseconds?Yousimplywon'tnoticethatthedatahasbeenupdatedthousandsoftimesifyouonlycheckyourdashboardonceanhour. Thatwasavaluablepointtomakethen.But,whileitcertainlyisstillinterestingtoconsiderwhatright-timemaymean,businesstrulymovesmorerapidlynow.Right-timeis,increasingly,real-time.Tokeeppace,moreorganizationsaremakingthatinvestmentinreal-timedataanalyticssodataisavailabletobeanalyzed,interpretedandvisualizedasitiscreatedorchangesintheirsourcesystems. Withsuchissuesinmind,whatarethebusinessbenefitsofreal-timedataforanalyticsapplicationsandotheruses?Herearesixofthetopones. 1.Makedecisionsatthespeedofyourbusiness Muchofwhatwedointheworldofdatamanagement,BIandanalytics--evenwiththelatestdatascienceandadvancedanalyticstools--stillfallsundertherubricofthatoldtermdecisionsupport.It'sagooddescriptor:thesoftwaresupportsyouinmakingbetterdecisions. Thisarticleispartof Whatisdatascience?Theultimateguide Whichalsoincludes: 8topdatascienceapplicationsandusecasesforbusinesses 8typesofbiasindataanalysisandhowtoavoidthem Howtostructureandmanageadatascienceteam Download1 DownloadthisentireguideforFREEnow! AsIsuggestedabove,betterdecisionsdoneedtobefasterdecisionsasthepaceofbusinessincreases.Whenevenmodestbusinessesaretradinggloballyonline,it'snotgoodenoughtowaitforanovernightdatamanagementprocesstoreconcilethedatawarehouseinordertodeliverstandardizedreports.Businessteamsworkingremotelyorinternationallyneedthebestinformationcontinuously,moreoftendeliveredinadashboardwithimmediateinsights. So,thefirst--andformanytheprimary--benefitofreal-timedataintheenterpriseissimplybeingabletosupportdecisionswheneverandwherevertheyneedtobemade. 2.Increasebusinessagilityandoptimization It'seasytofallintothetrapofthinkingthatfasterdecision-makingmeansamoreagilebusiness.Butinfact,businessagilityisn'tonlyaboutdecisions--agilityalsoencompassesyourstrategicandtacticalbusinessgoals.Choosingbetweenoptionsquicklydoesn'thelpwhenyoushouldbemakingchoicesofadifferentkind. Thebusinessbenefitsofreal-timeanalyticsinitiativesincludetheseitems. Oneapproachtobusinessagilitythathasprovenverysuccessfulinseveralindustrysectorsisthecreationofsmall,well-informed,tightlyfocusedteamscalledsquads.Forexample,retailersmayusesquadstofocusonproduce,homegoodsorotherspecificmerchandisecategories,empoweringthemtoquicklyanddirectlymakedecisionsthatpreviouslymighthaveinvolvedconsiderablemanagementreview.Manufacturersmayhavesquadsthatfocusonmaintenanceorsafety. Bygivingsquadsamandatetoactquicklysoclosetoyouroperations,youenablefasterand--hopefully--smarterresponsestoachangingbusinessenvironment.However,thisapproachcanonlybeeffectiveifasquadhastheneededdata,whichmustcontinuouslybekeptuptodatetomatchtheteam'surgency.That'sagreatusecaseforreal-timedata. 3.Quicklydetectandaddressoperationalissues Squadsstartedinthetechindustrybuthaveprovenpopularinsectorsfromretailtotelecomandeven,recently,healthcare--allbusinessesfacingrapidlychangingmarketsandcostpressures,alwayswithaneyetotheirprofitmargins. Youdon'tnecessarilyneedasquadtoimprovebusinessoperationswithreal-timedata.UsingdatafromIoTsensorsorvideofeedstomonitorproductionlinesforstoppagesandbacklogsandrunpredictivemaintenanceapplicationshasbeenpopularforseveralyearsnow.Itisaclassicexampleofreal-timeoperationalimprovementinactionandhasprovenveryeffectiveatreducingdowntimeinmanufacturingplants. Similarapproachescanbeappliedinquitedifferentscenarios.Forexample,real-timereportsoftrafficconditionsandweatherforecastscanhelplogisticscompaniesroutedeliverytrucksmoreeffectively.Ifthosetrucksarerefrigerated,onboardtemperaturesensorscanalsomonitorforissuesrequiringimmediateattentionorreroutingandsendreal-timealerts. Companiesalsousereal-timeanalyticstomonitorthebalanceofincomingordersandproductorpartsavailabilitysotheycanmovequicklytoincreasesuppliesthatarerunningshort,andtodetecttheneedforshort-termcontractlaborifproduction,packagingorshippingisfallingbehindtarget. 4.Identifyandactonshort-termmarketchanges Someindustriesareclearlysensitivetorapidmarketfluctuations--stocktradingisanobviousexample.Naturally,real-timedataisessentialtobusinesssurvivalinsuchcases. Otherindustries,suchasairlinesandhotelchains,managepricesandavailabilitybasedoncurrentevents,weather,oilpricesandotherfactorsthatcanchangerapidly.Today,withsomuchoftheretailexperiencetakingplaceonline,retailerstoohavetorespondquicklytochangingdemand,costsandcustomertrends. Real-timedataisinvaluabletoallthesescenarios.It'spossibletomovemoreslowlyifyourinventoriesandmarginsallowyoutotakeadeepbreathandridethroughsomedisruptions.However,fewbusinesseshavesuchluxurythesedays.Instead,wehavehadtobecomemuchsmarteraboutusingdatatoenablefasterandmoreefficientmonitoringofourmarkets. 5.Personalizethecustomerexperienceforonlinemarketing Onlineretailisaprimeexampleofhowreal-timedataenablesnewandmoreeffectivecustomerexperiences.Intheolddaysofthebrick-and-mortarstore,attentivestaffwouldrecognize,greetandguidetheregularandbestcustomers.Today,you'remorelikelytoberecognizedbyabotthathasaccesstoreal-timedatafromyouronlinebehavior.Andwhilethebotmaynotgreetyou,itcertainlywillensurethatthehomepage,specialoffers,recommendationsand,insomecases,eventhecolorschemereflectwhatithaslearnedaboutyouovernumeroussessions. Somepeoplethinkthisattentivenessandautomatedcustomizationcanbe"creepy"andalittletoofocusedforcomfort.Butthetruthis,numerousorganizationsusereal-timetechnologytopersonalizetheirwebsitesandonlineadvertisingforindividualcustomers,withoutpeopleevenrealizingthatitisworkingbehindthescenestoserveupwhattheythinkofasthenormalcustomerexperience. 6.Improvecustomerservicewithup-to-dateinformation Whetheryou'recallingcustomerserviceatyourutilitycompany,cableprovider,mobilenetworkoperatororairline,yourexperienceshouldbebetternowthanitwasjustafewyearsago.Why?Becausealloftheseindustries,andmanyothers,haveinvestedheavilyinreal-timedataintegrationfortheircallcenteroperations. Whencallcenteragentslookupsomeone'scustomerrecords,theyshouldbeabletoseeinformationonthelocaloutage,faultyequipment,unusuallyhighbill,canceledflightorotherissuethatpromptedthecall,rightthenasthey'retalkingwiththecustomer.Thiskindofinsightdrivenbyreal-timeapplicationsisstandardpracticenow. Collectingandmanagingreal-timedata It'sdifficulttogiveaconcisedescriptionofalltheprocessesinvolvedinreal-timedatamanagement.However,it'simportanttocallouttwosomewhatdifferentapproachestocollectingandmanagingdata:micro-batchingandstreaming. Mosttraditionaldatarepositories,suchasdatawarehousesandoperationaldatabases,areloadedwithdatainbatchesandrespondtoanalyticalquerieswithadatasetthatitselfisakindofbatch.Whenprocessingabatch,thereisabeginningandanend.Extract,transformandloadisthemostcommonformofdataintegration;I'veseenbatchETLprocessesthatranfor12hours,loadingadatawarehousewithmillionsofrecords.That'sabigbatch,anditwasalwaysareliefwhenitendedsuccessfully. Ifwewantnear-real-timedatacollection--onsometypeofperformancedata,forexample--wecanprocessmicro-batches,sometimesonlyonerecordatatime.Ifthedatamanagementenvironmentcanhandleit,thesemicro-batchescanbeprocessedintoandoutoftheanalyticssystemwithgreatrapidity,approximatingthereal-timedataatthesource.Nevertheless,micro-batchesstillhaveabeginningandanendandshouldhavesomeoftheadvantagesoftraditionaldataintegrationtechniques,suchasrobusttransactionhandlingintheeventofafailure. Likeaflowingriver,streamingdatahasnoclearbeginningorend.Thestreamingapproachisparticularlypopularwhencollectingreal-timedatafromsensors,suchastheonesindevicesconnectedtotheIoT,butstreamscanalsocomefromtransactionlogs,activitylogsandothersources. Forsimpletypesofanalytics,suchasreportingoncurrentconditions,monitoringforexceptionsandoutagesoroptimizingbusinessprocessesinresponsetoreal-timeactivity,streamingmaybeagreatoption.Agoodstreamingsystemiscapableofhandlingverylargevolumesofdata,alsomakingitsuitablefordatascienceapplications. However,ifit'simportanttointegratereal-timedatafromonesourcesystemwithtransactiondatafromanother,micro-batchingislikelyabettersolution.Forexample,handlingairlineticketsandre-bookingsintheeventofflightdelaysinvolveshighvolumesofrapidlychangingdata,buttheairlineneedstoensurethateachchangeinthesystemiscommittedsafelywithatransaction.Micro-batchingworksforsuchscenarios. Challengesofreal-timedataanalytics Therearesomerealadvantagesandbenefitstoreal-timedataanalyticsformanybusinesses.Butyouneedtobeawareofsomepotentialpitfalls.Eventhoughmostreal-timedataisnowprocessedandstoredinthecloud,thesheerscalethat'softeninvolvedrequiresspecialplanningfordatastorage.Indeed,muchofbigdata,whichcanincludebothstructuredandunstructureddata,isgeneratedbysourcesthatdrivereal-timeanalytics,suchaswebtrafficlogsandmanufacturingequipment. Youalsoneedtocarefullyconsideryourdataarchivingstrategyifthedecisionsbasedonthedataneedtobeauditedorreviewedforgovernanceandcompliance.Andyouneedtoplanoperationally,tacticallyandstrategicallyforproblemssuchassystemoutages,late-arrivingdataorotherreal-timeprocessingproblems. Nevertheless,witheffectivereal-timetechnologiesnowavailablefrommanyleadinganalyticsvendors,thereal-timestreamisrapidlybecomingmainstream. 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