沙利文- 新興亞太大數(shù)據(jù)市場(chǎng)研究報(bào)告 Emerging Asia-Pacific Big Data Market Research Report 2024（節(jié)選）

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