Sprint's Data Modernization Journey

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Transcript of Sprint's Data Modernization Journey

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SPRINT’SDATAMODERNIZATIONJOURNEYNovember30,2017

2 ©HortonworksInc.2011–2017.AllRightsReserved2 ©HortonworksInc.2011–2017.AllRightsReserved

3©2016 Sprint. Thisinformation issubject toSprint policies regarding use andisthe property ofSprint and/or its relevant affiliates andmaycontain restricted, confidential orprivilegedmaterialsintended forthesoleuseoftheintended recipient. Anyreview,use,distribution ordisclosure isprohibited without authorization.

10.1.2016Version 1.1DSB

Sprint’s Data Modernization JourneyPutting a foundational framework for empowering AnalyticsNovember 30, 2017

4©2016 Sprint. Thisinformation issubject toSprint policies regarding use andisthe property ofSprint and/or its relevant affiliates andmaycontain restricted, confidential orprivilegedmaterialsintended forthesoleuseoftheintended recipient. Anyreview,use,distribution ordisclosure isprohibited without authorization.

10.1.2016Version 1.1DSB

About Sprint

Sprintisoneofthelargesttelecomservices providers intheUSwithbusinessoperationsacrossmultiplecountriesofferingitsresidentialandcommercial

customersavarietyofcommunicationandmediaservices.

MultipleCountries-US,Mexico,Caribbean

Wireless,Internet,Prepaid,Wired

ServiceOfferings-B2B,B2C

60MSubscriberBase

5©2016 Sprint. Thisinformation issubject toSprint policies regarding use andisthe property ofSprint and/or its relevant affiliates andmaycontain restricted, confidential orprivilegedmaterialsintended forthesoleuseoftheintended recipient. Anyreview,use,distribution ordisclosure isprohibited without authorization.

10.1.2016Version 1.1DSB

Our Modernization Demand Drivers

ParadigmShiftinCustomerUsage– DatanowoutpacesVoiceusageenormously

DataExplosion– Moredataoriginatingfromall

directionsandnewtypes

IncreasedAppetiteforAnalytics– CostSavings,

BetterCustomerExperience

Wewereexperiencing aparadigmshiftinhowthedatalandscapewasevolvingandourfocuswasonhowwecanharnessthewealthofdata to

betterserveourcustomersandimproveourbusinessoperations.

6©2016 Sprint. Thisinformation issubject toSprint policies regarding use andisthe property ofSprint and/or its relevant affiliates andmaycontain restricted, confidential orprivilegedmaterialsintended forthesoleuseoftheintended recipient. Anyreview,use,distribution ordisclosure isprohibited without authorization.

10.1.2016Version 1.1DSB

Our Modernization Goals

Ourdatamodernizationgoalswerefocusedonbusiness imperatives inordertoprovidearicher,personalized customerexperience, improvebusiness

operationsandgainbettervisibility intoourCustomers.

Frauddetection– Expandeddatasetsandimprovedata

availability

Improvevisibilitytogainbetterinsightsandmaketimelybusinessdecisions

360DegreeViewofCustomer– betterwaystoserveandreducechurn

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10.1.2016Version 1.1DSB

Iterative Approach to Modernization

Wetookaniterativeapproach towardsmodernization inordertoensureourjourneyhadmeaningfulandachievable targets.

Buildfoundationalframeworkwithanevolvingandscalable

architecture

Reducedataredundancybyconsolidatingdatapoints

andimprovedataavailability

Spendlesstimeonlift&transformandmoreon

Analytics

CoreFoundation DataConsolidation EmpowerAnalytics

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10.1.2016Version 1.1DSB

Tips for Modernization

• Analysis and scoping• Big data is not just volume but also more compute and analytics• Scalable hardware which can be improved for more compute when required• Network throughputs or improve bandwidth for large data volumes

• Prepare and plan • Technology and Business Teams Adoption• Plan real-time architecture ahead instead of rearchitecting later

• Communicate and manage expectations

Thinkbig,startsmall,movefast.

10©2017DiyottaInc.AllRightsReserved.

Webinar:DataModernizationPlanBig,StartSmallandMoveFast

November30,2017

©2017DiyottaInc.AllRightsReserved.

What’sDrivingModernizationForYou?

ExpandedDataSets

Gettingaccesstothedatawhichwasnotaccessiblebefore

BetterComputing

Transformingdatainthemostoptimizedcomputeengine

DataAvailability

Gettingaccesstoactionabledataatthe

righttimetoact

AdvancedAnalytics

Gaininginsightsforbetterbusiness

decisionsinreal-time

CloudStrategy

Cloudbasedsources,computeincloudordatalakeincloud

ModernDataArchitectures

Moredatasources

Moreprocessingzones

Moredownstreamorconsumerapplications

Emergingtechnologies

Multipledevelopmentpatterns

WhatMattersforDataModernization

• TimetoValue• DataLatency• DataConsumption• Cost

Technology• Performance• Scalability• Maintainability• EvolvingTechnologiesEnablement

Business

ModernDataStrategyConsiderations

InvestinbuildingacoreArchitecturalFramework

withmoderndatasolutions

Leverageexistingteamstowardsbuildingin-houseexpertisefor

moderntechnologies

Augmentteamswithdomainexpertisetoleverageindustryperspective

DiyottaEnablesModernDataIntegration

ProvisiondataforAdvancedAnalytics

Acquiredatafromalldatapointsinbatchor

real-time

Chooseanycomputezonesfordataprocessing

Server-lessETLarchitecturewithnobottlenecks

Resources

DiyottaSolutionPage:http://www.diyotta.com/solutions

ModernDataIntegrationWhitepaper:https://www.diyotta.com/modern-data-integration-white-paper/

RequestDemo:http://www.diyotta.com/demo

DiyottaTestDrive:http://www.diyotta.com/try

PietLoubserVPProductandSolutionsMarketingHortonworks

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TheNewWayofBusinessIsFueledByConnectedData

• ConnectedCustomers,Vehicles,Devices

• Sociallycrowd-sourcedrequirements

• Digitaldesignandanalysis

• Digitalprototypesandtests(simulations)

• ConnectedFactories,Sensors,Devices

• Human-roboticinteraction

• 3D-printingondemand

• ConnectedTrucks,Inventory

• Location,traffic,weather-awaredistribution

• Real-timeinventoryvisibility

• Dynamicrerouting

• ConnectedCustomers,Devices

• Omni- channeldemandsensing

• Real-TimeRecommendations

• ConnectedAssets• Remoteservicemonitoring&delivery

• Predictivemaintenance

• OTAUpdates

Development Manufacturing Distribution Marketing/Sales Service

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ModernDataArchitecture

Telemetry–ConnectedDevices

Time–SeriesHistorian

MachineLearning

C LOUD Sensors,SCADA,

ControlSystems

EdgeAnalytics

ExceptionsthatDrivePredictiveMaintenance

360ViewofOperations,Equipment

FailureAnalytics,etc.

DeepHistoricalAnalysis

DATA C E N T E R

StreamAnalytics

Cyber&Threat Data

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ManyorganizationsstruggletounderstandthedifferencebetweenBigDataandBigBI

BigBusinessIntelligencevs.BigData

BigBI DATA BigData

§ Sameanalysisasbefore, justmoredata

§ Batchorwarehouse-typeprocessing

§ Informative,butnot reallyactionable

§ Joiningdatasetsneverbeforejoined, askingquestionsneverbeforeasked

§ Real-timeornearreal-time,leading topredictive/persuasive/preventive

§ Ability toextractthevalueofdataandquickly translateintoaction– ”DataAgility”

§ Action-oriented, driving“ActionattheSpeedofInsight”ManyapplytraditionalreportingmethodstoBigData&Advanced

Analyticsresultinginmissedopportunitiesandlimitedfinancialreturn

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EDWOptimization patterns:3UseCases

• ActiveArchiving

• ETLOffloading

• DataEnrichment

ANAL

YTICS

DataMarts

BusinessAnalytics

Visualization&Dashboards

DATASYSTEMS

SystemsofRecord

RDBMS

ERP

CRM

Other

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EDWPlusHortonworksDataPlatform(poweredbyApacheHadoop)OptimizeandReduceCosts

Archive Cold Data away from EDW• MovecoldorrarelyuseddatatoHadoop

asactivearchive• Storemoreofyourdatalonger,cheaper• Greaterhistoricalanalysis

Offload costly ETL process• FreeyourEDWtoperformhigh-valuefunctionslike

analytics&reporting,notETL

• UseHadoopforadvancedormassive-scaleETL/ELT

ANAL

YTICS

DATASYSTEMS

DataMarts

BusinessAnalytics

Visualization&Dashboards

SystemsofRecord

RDBMS

ERP

CRM

Other

ELT

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ColdData,DeeperArchive&NewSources

EnterpriseDataWarehouse

Hot

DataScience

OLAPonHadoop

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EDWPlusHortonworksDataPlatformandHortonworksDataFlowLandandEnrichmoredatatorespondfastertonewbusinessrequests

Archive Cold Data away from EDW• MovecoldorrarelyuseddatatoHadoop

asactivearchive• Storemoreofyourdatalonger,cheaper• Greaterhistoricalanalysis

Offload costly ETL process• FreeyourEDWtoperformhigh-valuefunctionslike

analytics&reporting,notETL• UseHadoopforadvancedormassive-scaleETL/ELT

Land & Enrich more data to create more value-add analytics

• UseHadooptoingestnewdatasources,suchaswebandmachinedatafornewanalyticalcontextfromunstructuredandsemi-structuredsources

• Createananalyticalsandbox foradvanceddatascience

ANAL

YTICS

DATASYSTEMS

DataMarts

BusinessAnalytics

Visualization&Dashboards

SystemsofRecord

RDBMS

ERP

CRM

Other

ELT

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°

°

°

°

°

°

°

°

°

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ColdData,DeeperArchive&NewSources

EnterpriseDataWarehouse

Hot

DataScience

OLAPonHadoop

Clickstream Web&Social Geolocation Sensor&Machine

ServerLogs

Unstructured

NEW

SOUR

CES

Ingest Stream Events

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AdvantagesofLeveragingtheHortonworksSolutions

DeeperandBroaderDataSets

CompleteDataGovernance&Security

RichandOpenAnalyticTools

Non-structuredandStructureddata

LowerTotalCostofOwnership

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M A X I M U M C O M M U N I T Y I N N O V A T I O N

T H E I N N O V A T I O N A D V A N T A G E

P R O P R I E T A R Y H A D O O P

T I M E

INN

OV

AT

ION

Innovationhappensbestnotinisolationbutincollaboration

OPENCOMMUNITY

OurFoundingBelief

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M A X I M U M C O M M U N I T Y I N N O V A T I O N

T H E I N N O V A T I O N A D V A N T A G E

P R O P R I E T A R Y H A D O O P

T I M E

INN

OV

AT

ION

Innovationhappensbestnotinisolationbutincollaboration

OPENCOMMUNITY

OurFoundingBelief

UnmatchedEconomicsEnablecosteffectivedata-centerandcloudarchitectures

MinimalVendorandIntegrationRiskspreventsvendorlock-inandspeedsecosystemadoptionofODPi-compliantcore

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ThankYou