#oowbr big data strategy: colocando os dados no caminho certo
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BigDataStrategy:PuttingDataontheRightTrackSES11934,October28,2015ChrisLynskey,VicePresident,ProductManagementMarcosArancibia,ProductManager,OracleDataScienceLuizGondim, HeadofInnovation,AmbevBrunoGurgel,ManagerofAnalytics&Insights,Ambev
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Data &Analytics
Technology4
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Data &Analytics
OracleBig DataPlatform
Focusonwhatmattersmost
5
SimplifyDataManagement
InnovateDataLab
IntegrateDataFactory
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OracleBigDataCloudServicesBigDataPlatform
FastData
DataFactory
DataLab
DataManagement
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SamePlatformYouUseinYourDatacenter100%UpwardCompatibilitywithOn-PremisesEnablesEasyCoexistenceandMigration
OracleCloud
CoExistence andMigration
Same Architecture
Same Standards
Same Products
Transparentlymoveworkloadsbetweenon-premisesandpubliccloud
PrivateCloud
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Ourdatamanagementplatformhasanalytics
DataLabCopyright©2016,Oracleand/oritsaffiliates.Allrightsreserved.| 9
BigData
DataMining
AnalyticalSQL LogAnalytics
Graph
RAnalytics
BigDataDiscovery
Spatial
StreamAnalytics
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DataManagementServices
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QueryallyourData:Hadoop,NoSQL&Relational
ExtendingDataManagement
NoSQL
{MapReduce} {APIs} SQLOracleBigDataSQLSQL RESTPython GraphRnode.js Java
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ExtremePerformanceinspiredbyExadataSmartScantechnology
OracleBigDataSQL:Fast polyglotdataaccess
OffloadQuerytoExadata StorageServers
Smalldatasubsetquicklyreturned
OffloadQuerytoDataNodes
SQL
datasubset
SQL
SimplyAccesstoAllData
Hadoop,NoSQL&Relational
NoApplicationChangesRequired
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UsestandardOracleSecurityoverHadoop&NoSQL• Grant&RevokePrivileges• RedactData• ApplyVirtualPrivateDatabase
• ProvidesFine-grainAccessControl
ExtendOracleDataManagementSecurityUsingOracleBigDataSQLwithOracleDBSecurity
Redacteddatasubset
SQL
JSONdataunconvertedin Hadoop
JSON
CustomerdatainOracleDB
DBMS_REDACT.ADD_POLICY(object_schema => 'txadp_hive_01',object_name => 'customer_address_ext',column_name => 'ca_street_name',policy_name => 'customer_address_redaction',function_type => DBMS_REDACT.RANDOM,expression => 'SYS_CONTEXT(''SYS_SESSION_ROLES'',
''REDACTION_TESTER'')=''TRUE''');
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BigDataLabsFuelEnterpriseInnovation
identifynewcustomersegments
predictnewproductsuccess
detectfraudulentactivity
bettermanagerisk
createinnovativeproductsandservices
optimizepricing
KeyPrincipalsoftheDataLab
collectsnewandexistingdataasrawmaterials
providesbroadaccesstoatrustedcommunity
enablesagileexperimentation,abilitytofailfast
offersa‘doanything’sandboxenvironment
DifficulttoUnlockDataLabforMoreUsers
DataLabiscurrentlytherealmoftheelusive
DataScientist
RawtoolsandcomplexlanguagesimpairBusiness
AnalystandSMEproductivity
?
CitizenDataScientistsNeedSomethingNew
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quicklytransformandenrichittomake
itbetter
unlockbigdataforanyonetodiscoverandsharenewvalue
Asingleintuitiveandvisualuserinterface,to...
findandexplorebigdatatounderstandits
potential
find explore transform discover
OracleBigDataDiscovery
find explore transform discover
Find
• AccessaninteractivecatalogofallinformationintheDataLab
• Familiarsearchandguidednavigationforeaseofuse
• Seedatasetsummaries,userannotationandrecommendations
• Self-servicedataloadforfilesanddatabases
Explore
• Visualizeallattributesbytype
• Sortattributesbyinformationpotentialandinformationgain
• Assessattributestatistics,dataqualityandoutliers
• Usescratchpadtouncovercorrelationsbetweenattributes
Transform
• Intuitive,userdrivendatawrangling
• Extensivelibraryofpowerfuldatatransformationsandenrichments
• Previewresults,undo,commitandreplaytransforms
• TestonsampledatathenapplytofulldatasetusingApacheSpark
Discover
• Joinandblenddatafordeeperperspectives
• Composeprojectpagesviadraganddrop
• Usepowerfulsearchandguidednavigationtoaskquestions
• Seenewpatternsinrich,interactivedatavisualizations
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OracleBigDataAdvancedAnalyticsIncludedinBigDataCloudService
OracleRforBigData• Scalable,distributedanalyticsforBigData
• Statistics&AdvancedMatrixComputation
• DistributedMachineLearningModelsonSpark
OracleSpatialAnalysis• Proximityandcontainmentanalysis
• LocationDataEnrichment• Vectorandrasterdatapreparation
OracleGraphAnalysis• PropertyGraphs• SocialMediarelationships• Churnanalysis• Cyber-Security• Objectrecognition
unlocking thepowerofINNOVATIONWITH
ANALYTICS
June 28th, 2016
CurrentLocation:LAN– SaoPaulo
FunctionalArea:IBS– DirectorofInnovation&Analytics
Timewiththecompany:15years
ABInbevCareerSummary
LAN– SalesManagerSaoPaulo,DistrictManagerJoaoPessoa&SPOeste,RegionalSoft
DrinkManagerSaoPaulo,TechSalesNationalManager,IBS– HeadofInnovation,IBS–
Sales&MKTCorporateManager
GHQ– Global SalesProcesses&TechnologyDirector
Luiz H. GondimDirector of Innovation & Analytics
AMBEVEBITDA (R$ MM) and EBITDA Margin Evolution
10%
15%
20%
25%
30%
35%
40%
45%
50%
55%
0
5
10
15
20
25
Billion
s
Series2
Series3
22,210
24%
48%
CND
660
Source: Company reports.
R$ 22.2 bn EBITDA
47.5% EBITDA Margin
2015 RESULTS
EBITDA R$
% consolidated EBITDA
Brazil
14,101 MM
64%
2,057 MM
9%
Canada
Latin America
South
4,878 MM
22%
Central America
and Caribbean
1,174 MM
5%
AMBEVToday
Source: Company, 2015 figures
2015 RESULTSEBITDA R$% consolidated EBITDA
Brazil14,101 MM64%
Source: Company, 2015 figures
BRAZILBiggest growth opportunity
Source: Company, 2015 figures
BRAZIL: SOLID STRUCTURAL DRIVERS + NEW CONSUMER TRENDSSignificant growth opportunities ahead of us
PositiveDemographics
Per CapitaGrowth
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
AMBEV WELL POSITIONED TO CAPTURE THESE GROWTH
OPPORTUNITIES
Strong brands
Local execution,
global expertise
Leading
market shareTalented and
motivated people
Unparalleled
distribution footprint
Complete portfolio
mainstream to high end
Nimble and fast to react
Connectivity and processing powerBillions of people connected on the go, unprecedented processing power, storage, and knowledge accessTechnology
& information revolution
Transformation of the human condition, fundamentally changing the way we live, work, and relate to one another
Disruptive innovations Emerging breakthroughs across all fields (AI, Robotics, IoT, 3D printing, nanotech, quantum computing, etc.)
Amplifying building blocksTechnologies amplify each other in a fusion of technologies across physical, digital & biological worlds
New business modelsEmergence of new business models disrupt incumbents through reshaping production, consumption and delivery models
Accelerating changesChanges are historic in size, speed and scope. Speed of change increases exponentially
The technology & information revolution is creating new challenges and new opportunities for companies to disrupt and innovate
BeingSocial
BeingSocial
INNOVATION
Innovation
“Thenextdecadeofmarketingwillbetightlylinkedwithcreatingarelevantcustomerexperienceacrosschannelsanddeviceswherepeopleengage.Asaresult,wewilllearntothinkwellbeyondbuyingaudiencesandshiftourfocustomarketingtopeople.”
James Green, MediaPost, August 6th, 2015
ConsumerGoldenRecord
CONSUMER 1 TO 1 VISION: FROM CHANNELS AND AUDIENCES TO DEVICES AND PEOPLEPOINTS
35
By 2018, there will be nearly four billion global
Internet users (about 52% of the world’s
population), up from 2.5 billion in 2013
By 2018, there will be 21 billion networked devices and connections globally, up from 12 billion in 2013
Globally, the average fixed broadband
connection speed will increase 2.6-fold, from 16 Mbps in 2013 to 42
Mbps by 2018
Globally, IP video will represent 79% of all
traffic by 2018, up from 66% in 2013
36
DEVICES AND PEOPLE: THE CONNECTED CONSUMER SURROUNDED BY EXPLODING DEVICE LANDSCAPE
EXPERIMENTSAMPLES
BG
37
CurrentLocation:LAN– SaoPaulo
FunctionalArea:IBS–ManagerofAnalytics&Insights
Timewiththecompany:4years
ABInbevCareerSummary
LAN– IBSSpecialistforCRM,IBSSpecialistforTechMarketing,ITSpecialist- Innovations
Bruno GurgelManager of Analytics & Insights
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Actual Scenario
Ambev
POC|Retailer
Shoppers
Proposal
Ambev
POC|Retailer
Shoppers
Shopper Info
PurchaseExperience
TradicionalActivation
2
3
1
Activation Models
THE INDUSTRY DATA CHALLENGE
40
LEARNINGPOINTS
41
SOLUTIONDESIGN
Descoberta
42
SOLUTIONCOMPONENTS
43
SOLUTIONCOMPONENTS
44
ExternalSources
ModelingProcess
MIRAAPI(QueuesService)
IoT
OracleCloudStorage
SchedulerScriptsLiveSubmits
Sources(SitesandForms )
HDFS
SOLUTIONCOMPONENTS
Process
Modeling Process
HDFSOriginal Stores
DataOnboarding
DataOrganizationDataSetsModeling
TimeStampsMore…
Data1st EnrichmentBetweenSources
DataEnrichmentExternalSources
HiveTables
DataCleansing(Harmonization)
DataSwampLayer
DataLakeLayer
SOLUTIONCOMPONENTS
Process
SaaS PaaS
46
WHY ORACLE
TTM OpenSource
1. CreateandExecuteExperimentsalignedtostrategicbusinessneeds2. Transformsuccessfulexperimentsintoscalable,Globalcapabilities
3. Relationshipbuilding,community
4. ChampionInnovationCulture
5. GeneratetruevaluetoourConsumer
6. Talentacquisition
IBS INNOVATION & ANALYTICS RESPONSIBILITIES
47
THANKYOUBG
48