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EmergingAsia-Pacific
BigDataMarketReport,2024
GlobalCorporateGrowthConsultingCompany
Helpingclientsnavigatetowardsafutureshapedbygrowth
Anycontentprovidedinthisreport(includingbutnotlimitedtodata,text,charts,images,etc.)ishighlyconfidentialandtheexclusivepropertyofFrost&Sullivan(exceptwheresourcesareindividuallycitedinthereport).Nopartofthisreportmaybecopied,distributed,published,quoted,adapted,orcompiledinanyformwithoutpriorwrittenconsentfromFrost&Sullivan.AnyviolationoftheaboveagreementmayresultinlegalactionfromFrost&Sullivan.
October2024
ResearchMethodologyandSample
Researchbasedonawidesamplebase:Classificationstatisticsbydownstreamcustomerindustry,size,region,andcloudvendortype
HongKongSAR
DownstreamCustomerRegion
DownstreamCustomerIndustry
SingaporeIndonesiaUMalaysia
Thailand
PhilippinesSriLanka
aBangladesh
6.00%
LargeEnterprises,10%
6.00%
23.00%
Finance,25%
9.00%
10.00%
Internet,10%
Region/Scope
19.00%
Government,20%
12.00%
15.00%
Operators,20%
Telecom
CloudVendorType
Size
DownstreamCustomer
OtherCloudVendors,30%
<1000employees,20%
InternetCloudVendors,50%
>5000employees,45%
EmergingAsia-PacificRegion
TelecomCloudVendors,20%
1000-5000employees,35%
Note:
Thisstudyfocusesonthe"EmergingAsia-PacificMarket,"mainlyincludingHongKong,China;thePhilippines;Indonesia;Malaysia;Singapore;Thailand;Bangladesh;SriLanka.
Sources:Frost&Sullivan
Thesurveysamplesizeisasfollows:downstreamcustomersurvey,30companies;cloudvendorsurvey,15companies.
2
Contents
?1.BackgroundofBigDataDevelopmentintheEmergingAsia-PacificRegion
1.1MacroBackgroundofBigDataIndustryDevelopmentintheEmergingAsia-PacificRegion 4
1.2CurrentDemandforBigDataIndustryDevelopmentintheEmergingAsia-PacificRegion 5
?2.InsightsintotheBigDataMarketintheEmergingAsia-PacificRegion
2.1OverviewoftheBigDataMarketintheEmergingAsia-PacificRegion 6
2.1.1StagesofDevelopmentintheBigDataIndustryintheEmergingAsia-PacificRegion 7
2.2PainPointsofBigDataCustomersintheEmergingAsia-PacificRegion
2.2.1PainPointsintheTelecomSector 8
2.2.2PainPointsintheFinancialSector 9
2.2.3PainPointsintheGovernmentSector 10
2.2.4PainPointsintheInternetSector 11
2.2.5PainPointsinLargeEnterprises 12
2.3KeyFactorsofConcernforBigDataCustomersintheEmergingAsia-PacificRegion 13
?3.FutureTrendAnalysisofBigDataDevelopmentintheEmergingAsia-
PacificRegion
3.1FutureTrendsoftheBigDataMarketintheEmergingAsia-PacificRegion 14
3.2FutureTrendsofBigDataTechnologyintheEmergingAsia-PacificRegion 15
?4.ComprehensiveCompetitivenessEvaluation
4.1CompetitiveLandscapeofBigDataServiceProvidersintheEmergingAsia-PacificRegion 16
4.2BigDataMarketShareRankings
4.2.1RankedbyIndustry 17-18
4.2.2RankedbyCountryandRegion 19-22
3
OverviewoftheEmergingAsia-PacificRegion
1
Economy&Society
2
3
Technology
MacroBackground:ThebigdatamarketintheemergingAsia-Pacificregionisinaphaseofrapidexpansion,showingtremendousgrowthpotential.
KeyFindings
?Nationalpoliciesandcross-bordercooperationprovidestrongmomentumforthebigdataindustryintheemergingAsia-Pacificregion.However,cross-borderdataflowsanddatasecuritycomplianceremainmajorchallengesfortheregion'sdevelopment.
?Rapideconomicgrowthandsupportfromcapitalmarketshaveboostedtheapplicationandinnovationofbigdatatechnologies,butthelonginvestmentreturncyclehasputprofitabilitypressureonsomeenterprises.
?Themomentumofdigitaltransformationamongenterprisesisstrong,withthedeepintegrationofcloudcomputing,bigdata,andAItechnologiesdrivingimprovementsinefficiencyandcompetitiveness.However,duringtheprocessofmigratingbusinesstothecloud,complextechnicalchallengesrelatedtodataintegration,processing,andanalysis,aswellasprivacycomplianceissues,arise.
Advantages:
?NationalStrategicDrivers:GovernmentsofmanyemergingAsia-Pacificcountriesareactivelypromotingthedevelopmentofthebigdataindustry,incorporatingbigdataaspartofnationalstrategy.Thesepoliciesprimarilyfocusonsupportingtechnologicalinnovation,ensuringdatasecurity,promotinginternationalcooperation,andcultivatingprofessionaltalent,drivingtheapplicationofbigdatatechnologiesacrossvariousindustries.Forexample,theIndonesiangovernment,throughtheformulationofthe"2023-2045DigitalIndustryDevelopmentMasterPlan,"hascollaboratedwithinternationaltechnologycompaniestolaunchtrainingprogramsspecificallytargetingbigdataanalyticsanddatascience,andestablishedanationaldatacentertobridgetheskillsgapandenhancethecapabilitiesofdigitaltalent.
?Cross-borderCooperationinBigDataTechnology:EmergingAsia-Pacificcountriesarepromotingcross-bordercooperationinbigdatatechnologythroughregionalorganizationsandagreements.Forexample,theAsia-PacificEconomicCooperation(APEC)emphasizesthenecessityofdatasharingandcross-borderdataflowinitsdigitaleconomyagendatofacilitatetheintegrationoftheregionaldigitaleconomy.Additionally,ASEANcountrieshavestrengthenedcooperationinthedigitalsector,promotingdataeconomyintegrationandcreatingamoreopenpolicyenvironmentforthedevelopmentofthebigdataindustry.
Challenges:
?RestrictionsonCross-borderDataFlow:Differentcountrieshavevaryingstancesandregulationsregardingcross-borderdataflow.Somecountriesimposestrictrestrictionsoncross-borderdatatransfers,whichmayaffecttheefficiencyofglobalcompaniestransmittingdatabetweencountries.SuchrestrictionscanhindertheadoptionofbigdatatechnologiesintheAsia-Pacificmarket.Forinstance,underMalaysia'sPersonalDataProtectionAct(PDPA),itisstrictlyregulatedthatpersonaldatacannotbetransferredabroadwithoutapproval.Cross-borderdatatransfersareonlyallowedifthereceivingcountryprovidessufficientdataprotectionorwiththeexplicitconsentofthedatasubject.
Policies
Advantages
RapidExpansionoftheDigitalEconomy:ThedigitaleconomyintheemergingAsia-Pacificregionisrapidlyexpanding,withboomingdigitalindustriessuchase-commerce,fintech,andtheInternetofThings(IoT),drivingdemandfordatacollection,processing,andanalysis.Thiseconomictransformationprovidesvastdevelopmentopportunitiesforthebigdataindustry.
DemographicDividend:TheemergingAsia-Pacificregionhasalargepopulation.Asof2023,theregion'spopulationaccountedforapproximately9%oftheglobalpopulation,roughly720millionpeople.Additionally,theregionhasalargenumberofinternetusersandsmartdeviceusers.By2023,theinternetpenetrationrateintheregionwasabout66%,anincreasefrom61%in2021.Althoughpenetrationratesvarybycountryandregion,thisgrowthreflectstheregion'sprogressininternetusage.Consequently,withtheincreasinginternetpenetrationandwidespreaduseofmobiledevices,theregionisgeneratingmassiveamountsofbigdata.Moreover,thelargepopulationbaseandrapidurbanizationprovideafoundationfordatacollectionandutilization.
Challenges
?AsymmetryBetweenInputandOutput:Whilebigdatatechnologiesofferhighreturns,theinitialinvestmentisalsorelativelyhigh,particularlyinbuildingdatainfrastructure,datacollectionandstorage,andresearchanddevelopment.Thisrequirescompaniestohavestrongfinancialcapacityandbepreparedforlong-termreturns.
Advantages
IncreasedCorporateTechnologyInvestment:BenefitingfromthedigitaltransformationintheemergingAsia-Pacificmarket,thespreadofcloudcomputing,andthedevelopmentofAI,companiesareincreasingtheirspendingontechnologyinvestments,particularlyinfieldssuchasbigdataanalytics,machinelearning,andartificialintelligence.
DigitalTransformationofEnterprises:Drivenbyglobalcompetitivepressuresandtechnologicalinnovation,companiesintheemergingAsia-Pacificregionareundergoingdigitaltransformationtoimproveoperationalefficiencyandmarketcompetitiveness.Bigdatatechnologiesarewidelyappliedinindustriessuchasmanufacturing,financialservices,retail,andhealthcare,helpingcompaniesmakedata-drivendecisionsinproduction,sales,andcustomerservice.
Challenges
?ChallengesofDeepeningCloudUtilization:AsdigitaltransformationacceleratesintheemergingAsia-Pacificregion,enterprisesaremovingfrominitialcloudadoptiontomorein-depthutilizationofcloudcomputing
resources.Inthisprocess,bigdatahasbecomeakeydriverforbusinessinsightsandinnovation,placingnewdemandsoncloudplatforms.Companiesexpecttoleveragecloudcomputingforbusinessagilityandinnovationbut
alsofacechallengesrelatedtodataprocessingcapabilities,security,andcostefficiency.Sources:ASEANBRIEFING,opengovAsia,ERIA,F(xiàn)rost&Sullivan
4
CurrentDevelopmentStatusandDrivingFactorsofBigDataIndustriesinVariousCountriesandRegions
ThebigdataindustryintheemergingAsia-Pacificregionhassignificantdevelopmentpotential,supportedbyfavorablepoliciesand
Asakeyinternationalcenterforfinance,trade,shipping,andcommunicationsinChina,HongKongcanleverageitsuniqueadvantagesunderthe"OneCountry,TwoSystems"frameworkanditsstatusasa"domesticyetinternational"regiontoenhanceitsdigitalcapabilitiesthroughdata-drivenapproaches.ThiswillboostHongKong’sdevelopmentininnovationandtechnology,thedigitaleconomy,andsmartcities,contributingtothecreationofamorelivable,competitive,andsustainablecity.TheseeffortsalsopositionHongKongasaninternationaldatahub,promotingthegrowthofindustriesthatmergedomesticandforeigndatainHongKong.
Accordingtothe2023PolicyAddressbytheChiefExecutiveofHongKong,thecityiscommittedtopromotingdatagovernanceandthedevelopmentofadigitalgovernment.Thegovernmentplanstofurtherdeveloptheinnovationandtechnologyecosystembystrengtheningthemanagementofdataflowsanddatasecurity.Additionally,HongKongwillestablishasupercomputingcentertosupportthedevelopmentofartificialintelligenceandbigdataapplications.
HongSAR
Kong?
SriLanka
?SriLanka'sbigdataindustryisstillinitsearlystages,butwiththecountry’sdigitaltransformationinitiativesandinvestmentsininformationtechnologyinfrastructure,theindustryshowsgreatpotential.
?BigdatahasseeninitialapplicationsinseveralindustriesinSriLanka,particularlyinfinancialservices,healthcare,retail,andgovernmentsectors.TheBanking,FinancialServices,andInsurance(BFSI)sectorandthegovernmentanddefensesectorsarethemainusersofbigdataanalytics,helpingtheseareasimproveoperationalefficiencyandservicelevels.
promisingprospects.
Malaysia
?Malaysia'sbigdataindustryisdevelopingrapidly,drivenbygovernmentpolicies,theconstructionofdigitalinfrastructure,andincreasingmarketdemand.
?
Philippines
?AccordingtotheMalaysiaDigitalEconomyBlueprint,theMalaysiangovernmentisadvancingdigitaleconomicdevelopmentthroughtheMyDigitalinitiative,withagoaltohavethedigitaleconomycontribute22.6%(laterrevisedto25.5%)ofGDPby2025.Thisplancoverstheapplicationofbigdataacrossvariousfields,includingcloudcomputing,governmentdigitaltransformation,andsmartcitydevelopment,promotingthewidespreaduseofbigdatatechnologiesamongbusinessesandgovernmentinstitutions.
?ThePhilippinespossessesvastamountsofdataandbusinessactivities,andboththegovernmentandenterpriseshavebegunutilizingcloudandAItechnologiestoanalyzedata,improvingoperationalefficiency,reducingcosts,andenhancingthequalityofoperationsanduserexperience.
?AccordingtothePhilippineStatisticalDevelopmentProgram(PSDP)2018-2023,thePSDPaimstopromotetheapplicationofbigdatatosupportgovernmentpolicy-makingandplanningbystrengtheningthecapacityofthePhilippineStatisticalSystem(PSS).Bigdataisseenasacrucialfoundationforfutureproductivityandinnovation.ThePSDPpromotestheintegrationandanalysisofbigdata,administrativedata,andcitizen-generateddatathroughthetrainingofstatisticiansintheuseofopen-sourcesoftware.Additionally,theprogramplacesspecialemphasisontheSustainableDevelopmentGoals(SDGs),supportingtheirimplementationandmonitoringthroughtheuseofbigdataand
?TheMalaysianSupremeCourtutilizesacomprehensivedatabackupsolutionfore-governanceandroutinedocumentmanagement.
Bangladesh
otherstatisticalresources.
Indonesia
?ThebigdataindustryinBangladeshisinaphaseofrapiddevelopment,stronglysupportedbygovernmentpolicies.TheBangladeshigovernmentlaunchedthe"DigitalBangladesh"initiativein2009,aimingtodrivethecountry'sdigitaltransformationthroughInformationandCommunicationTechnology(ICT)andpositionBangladeshasakeyplayerintheglobaldigitaleconomy.By2041,thegovernment’sgoalistotransformthecountryintoa"knowledgeeconomy."Thisstrategyemphasizesthedevelopmentoftechnologiessuchasbigdata,artificialintelligence,theInternetofThings(IoT),andblockchain.
?Indonesia,withitslargepopulationandfasteconomicgrowth,stillhasuntappedpotentialininternetpenetration,providingampleopportunitiesfortheintegrationofbigdataandcloudcomputing.Additionally,theIndonesiangovernmenthasmadethetechnologyindustryakeypartofitsdevelopmentstrategy,aimingtoleveragedigitaleconomicgrowthtobecomeoneoftheworld’stopteneconomies.Withpolicysupportandinherentadvantages,foreigncloudserviceprovidersandtechcompanieshavesuccessfullylocalizedtheiroperationsinIndonesia.
Thailand
?In2022,theThaigovernmentapprovedtheestablishmentoftheNationalBigDataInstitute(BDI),replacingthe
?Singaporeboastsexcellentinfrastructure,includingtheworld’sbusiestcontainerport,top-ratedairportservices,andAsia’smostextensivebroadbandinternetsystemandcommunicationnetwork.However,italsofacesthepressureofexponentialdatagrowth,whichcreatesbroaderapplicationscenariosfortheintegrationofcloudcomputingandbigdata.Thishelpsaddresstheincreasingdemandfordataprocessingandfostersthehealthydevelopmentofcloudservicesandthedigitaleconomy.
?AccordingtotheSingaporeDigitalEconomyReport2023,thedigitaleconomycontributed17.3%ofSingapore'sGDPin2022,amountingtoapproximatelySGD106billion,demonstratingtheimportanceofbigdataindrivingeconomicgrowth.BypromotingthedevelopmentoftheInformationandCommunications(I&C)sector,Singaporehasstrengtheneditsdigitalservicescapabilities,suchascloudcomputing,data
Singapore
formerGovernmentBigDataInstitute(GBDi).TheBDIaimstopromoteeconomicandsocialdevelopmentthroughbigdataandprovidedataanalyticsservicesforbothgovernmentandprivateinstitutions.Theinstituteisalsoresponsibleforfosteringinnovation,particularlyintheanalysisofdatarelatedtohealth,environment,tourism,labor,andjusticesectors.
?BigdataisakeycomponentofThailand’s“Thailand4.0”strategy,whichaimstodrivethedigitaltransformationofindustryandtheeconomy.Overthenextfiveyears,theBigDataInstitutewillfocusonanalyzingdatainareassuchashealth,environment,andtourismtosupportgovernmentpolicy-makingandsocialdevelopment.
?AccordingtoIDC,thebigdataandanalyticssoftwaremarketinIndonesiagrewby14.7%inthefirsthalfof2022,indicatingincreasedenterpriseinvestmentinbigdatatechnologies,particularlydrivenbytheneedforcostoptimization,efficiencyimprovements,andaccesstonewmarkets.Thegovernmentisalsoencouragingdigitaltransformationacrossmoreindustriesthroughtheseinitiatives.
analytics,andsoftwaredevelopment.Sources:MalaysiaDigitalEconomyBlueprint,SingaporeDigitalEconomyReport,TheThaiger,HongKong2023PolicyAddressbytheChiefExecutive,Frost&Sullivan,WorldEconomicForum,AsianDevelopmentBank
5
BigDataMarketDefinition
Thebigdatasolutionsmarketreferstotheprocessofeffectivelycollecting,storing,computing,analyzing,andapplyingmassiveamountsofdatausingcomputerhardwareandsoftwaretechnologies.Thisprocesshelpsenterprisesextractvaluableinformationfromvastamountsofrawdatainrealtime,supportingbusinessdecision-making.
BigDataServiceClassificationStandards:Theclassificationstandardsforbigdataplatformservicesincludethediversityofdatacollectiontypes(handlingstructured,semi-structured,andunstructureddata),storagemethods(differentiatingbetweendatalakesanddatawarehouses),computationalcapabilities(supportingbatchprocessingandreal-timestreamprocessing),andintelligentanalyticscapabilities(integratingAIandmachinelearningfordatapredictionandoptimization).Thesestandardsensurethatplatformscanmeetcomplexanddiversebusinessneeds,coveringtheentireprocessfromdatacollectionandstoragetointelligentanalysis,helpingbusinessesachieveefficientdecision-makingsupportandbusinessoptimization.
KeyComponentsofBigDataServices:Thecorecomponentsofabigdataplatformincludemulti-sourcedatacollectionandintegration,datalakeanddatawarehousestorageandprocessing,AI-drivendataanalysisandprediction,andbusinessoptimizationbasedonanalysisresults.Thesecomponentsenablebusinessestoflexiblymanageandutilizedata,optimizebusinessprocesses,enhancemarketcompetitiveness,andimplementintelligentdatamanagementsolutions.
Dataiscollectedfromvarioussources
Dataentersthedatalakeforprocessingandaccess
Processeddataisusedforadvancedbusinessanalysis
AnalysisResultsUsedforBusinessOptimization
OptimizationModelsandRiskAssessment
(ModelArts,GoogleCloudAIPlatform,AzureMachineLearning)
AIandmachinelearningenablesmarterdatalakesbymodelingandpredictinglarge-scaledataindata
analysis.Thisenhancesthepredictiveandanalyticalcapabilitiesofdata,helpingbusinessesidentify
potentialpatternsandoptimizeoperationalprocesses.
AI+DataLake(DataArtsStudio,DeltaLake,GoogleBigQuery,
ApacheIceberg)
BycombiningAIanddatalake
technologies,enterprisescan
StructuredData
CreditcardnumbersDates
FinancialamountsPhonenumbers
leverageAImodelstoanalyze
massiveamountsofdatastoredindatalakes,automatetheprocessingofunstructureddata,andextract
valuablebusinessinsights.
…
Real-TimeDataWarehouseandBusiness
Intelligence(TeradataVantage,DWS,DLA,AzureSynapseAnalytics)
Withreal-timedataprovidedbyreal-timedata
warehousesandBIplatforms,businessescan
transformdataanalysisresultsintovisualcharts,
aidingmanagementinbetterunderstandingthedataandprovidingreal-timeinsights.
UnstructuredData
WebpagesEmails
SocialmediaplatformcontentAudio,video
DataLake(DLI,MRS,DataArtsStudio,AmazonS3,AzureDataLakeStorage)
Real-TimeBusinessResponse(CSS,TBDS)
Byutilizingreal-timesearchandlocatingspecificdata,theefficiencyofstructureddataretrievalisimproved,enablingbusinessestomakequick
decisionsandachieveagilebusinessoperations.
Alocationforstoringlargevolumesofstructuredorunstructureddatafrom
multiplesources
Enterprisesprocessandanalyzedataondemand
DataWarehouse(DWS,OracleExadata,IBMNetezza,Cloudera)
…
Ahigh-performancesystemusedforstoringandmanagingstructuredenterprisedata,focusingonsupportinglarge-scaledataanalysisandqueries,oftenusedforhandlinghigh-traffic,mission-
criticalbusinessdata.
Sources:Frost&Sullivan
6
DevelopmentStagesoftheBigDataIndustryintheEmergingAsia-PacificRegion
Bigdataplatformtechnologyhascontinuouslyevolvedfromdatabasetechnology,experiencingphasesofseparationandintegration.Facingchanging
businessdemandsintheAsia-Pacificregion,technologicalevolutionismovingtowardsintegration,essentiallycombiningtheadvantagesofvarioustechnologiestomeetthehigh-performanceandreal-timerequirementsofcomplexscenarios.
?TheRiseofDataWarehouses:DataWarehousesfirstappearedinthemid-1980s,designedtosupportcorporatedecision-makingbyintegratingstructureddata.Asdatavolumessurged,traditionaldatawarehousesstruggledwithscalabilityandcouldnotefficientlyhandlepeakdemand.IntheAsia-Pacificregion,especiallyinSingaporeandHongKong,theapplicationofdatawarehousetechnologyhasmatured,andenterpriseshavebegunadoptingclouddatawarehousesolutionstoenhancedataprocessingcapabilitiesandreducecosts.
?TheEmergenceofDataLakes:DataLakeshaverisenasanewdatastoragesolution,capableofhandlingbothstructuredandunstructureddata,offeringgreaterflexibility.Theyallowenterprisestostoredatawithoutpredefiningitsstructure,thoughgovernancechallengeshaveimpactedtheefficiencyofdataqueryingandmanagement.InIndonesia,e-commerceandfintechcompaniesleveragedatalakestooptimizeoperations,improvecustomerexperiences,andenhancebusinessdecision-making.Similarly,Malaysiancompaniesareactivelyexploringtheapplicationofdatalakestoadapttorapidlychangingmarketdemands.
?IntegrationofDataLakesandWarehouses:Inrecentyears,theDataLakehousearchitecturehasemerged,combiningtheflexibilityofdatalakeswiththestructuredmanagementadvantagesofdatawarehouses.Thisarchitectureeliminatesdatasilosbetweenlakesandwarehouses,enablingseamlessdatamanagementwithlow-coststorage,withoutdatamigration,andwithefficientdataflow.HuaweiCloudhasenhancedtheLakehousearchitecturewithintegratedbatch-streamprocessing,enablingreal-timedataanalyticswheredataisupdatedinthelakeinseconds,allowingreal-timedataretrievalandsignificantlyimprovinguserexperiencesfromT+1toT+0.InThailand,manufacturingenterprisesaregraduallyadoptingtheLakehousearchitecture,usingreal-timedataanalyticstodrivesmartmanufacturinganddigitaltransformation,improvingproductionefficiency.
?TheRiseofIntelligentDataLakes:IntelligentDataLakescombineartificialintelligenceandbigdatatechnologiestoautomatedatamanagementandanalysis,enhancingdatautilizationandinsights.Huawei’sIntelligentDataLakeoperationalplatformisaprimeexample,providingintelligentdatagovernanceandanalyticstohelpenterprisesquicklybuilddataoperationscapabilitiesandmaximizethevalueoftheirdataassets.IntheAsia-Pacificregion,SingaporeanenterprisesareattheforefrontofIntelligentDataLakeadoption,usingAItechnologiesfordataprocessingandanalysistosupportintelligentdecision-makingandbusinessinnovation.
ClassificationofBigDataPlatformTechnologyEvolution
19701998201220142020
NoSQL
RelationalDatabase
NewSQL
HTAP
CloudNativeDatabase
1980
MPPArchitecture
2010
DataLakeConcept
AILargeModel+DataLake
Open-sourceDataLakes
(Deltalake、Hudi、iceberg)
2006
CloudComputing
2021-Present
IntelligentDataLake
1980-1991
DataWarehouseTheory
DataLake
DataLakehouse
Database
2013-2017CloudNative
2010
2000
19602020
2013
SparkStreaming
DistributedStreamProcessing
DistributedBatchProcessing
2014Flink
2010Storm
2006Hadoop
2009Spark
2003-2006
GFS、BigTable
LimitedIndustryDigitalization
MapReduce
Internet
Riseofthe
RiseofMobileInternet
Small-scale,structureddataanalysisandprocessingLarge-scale,unstructureddataanalysisandprocessingEfficientandintelligentanalysisandprocessingoflarge-scale,unstructureddata
Source:ChinaAcademyofInformationandCommunicationsTechnology,Frost&Sullivan
7
CustomerScenarioAnalysisoftheBigDataIndustryintheEmergingAsia-PacificRegion(TelecomOperators)
Addressingthechallengesofdataintegration,networksecurity,anduserexperiencefortelecomoperators:Bigdatatechnology
drivespreciseoptimization,enhancespersonalizedservices,andimprovesresourcemanagement.
PainPointsintheTelecommunicationsandTelecomOperatorsIndustry
ChallengesinDataManagementandIntegration:Asof2023,thetotalnumberofinternetusersintheemergingAsia-Pacificregion,particularlyinSoutheastAsia,reached442million,withaninternetpenetrationrateof78%,significantlyhigherthantheglobalaverageof67.5%.Indonesiahasthelargestuserbase,with205millionusers,whileSingaporehasthehighestinternetpenetrationrateat92%,followedcloselybyMalaysiaat89.6%.TelecomoperatorsintheemergingAsia-Pacificregionfacemassivevolumesofdata,withincreasingcomplexityinaggregatingdatafrommultiplesources(e.g.,networktraffic,userbehavior,devicedata).Theissueofdatasilosexacerbatesthischallenge,makingitdifficultfordifferentdepartmentsandsystemstosharedata,affectingtheeffi
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