• Save
Big Data Forum - Phoenix
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

Big Data Forum - Phoenix

on

  • 3,290 views

Big Data Forum at Salt River Fields (the spring training field for the Arizona Diamondbacks). Krishnan Parasuraman discusses how companies are using big data and analytics to transform their business. ...

Big Data Forum at Salt River Fields (the spring training field for the Arizona Diamondbacks). Krishnan Parasuraman discusses how companies are using big data and analytics to transform their business.

Statistics

Views

Total Views
3,290
Views on SlideShare
3,290
Embed Views
0

Actions

Likes
7
Downloads
0
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Big Data Forum - Phoenix Presentation Transcript

  • 1. IBM Big Data ForumSalt River Fields, Phoenix, Arizona16 May 2013Krishnan Parasuraman
  • 2. Talking PointsWhat is Big Data?1What is the relationship between Big Dataand Analytics?2What does a Big Data Platform look like?3What are the different entry points into Big Data?4What is IBM’s strategy in Big Data?5
  • 3. The number of organizations who see analytics as acompetitive advantage is growing.2010 2011 201263%
  • 4. IBM IBV/MIT Sloan Management Review Study 2011Copyright Massachusetts Institute of Technology 2011Studies show that organizations competing onanalytics substantially outperform their peers1.6xRevenueGrowth 2.0x EBITDAGrowth2.5x Stock PriceAppreciation4
  • 5. Analytics (by itself) = Blah.Analytics + Big Data = Kickass Competitive Advantage
  • 6. Big Data Analytics Use CasesCall CentersVoice-to-text mining for understandingcustomer sentimentHealthcareGenomics AnalyticsMedical Record AnalyticsE Commerce / RetailClickstream analyticsAnalyze online behavior and buying patternsOil and Gas / EnergyGeospatial AnalysisWindmill placements
  • 7. The Analytics Continuum…in HealthcareTransactionreporting• Evidence-based medicine• Personalized healthcare• Dynamic fraud detection• Patient, member behavior• Enterprise-wide data• Enterprise analytics• Clinical outcomes reporting• Unified data sources• Clinical data repositories• Departmental data marts• Dashboards• Spreadsheets• Separate data sources• Manual collation of data• Basic reportingData integrationData warehouseClinicalanalyticsAdvancedanalytics• What are the key health indicators across my patient population?• What are our quality scores ?• What is the total cost of care?• What is our productivity and resource utilization?
  • 8. The Analytics Continuum…in HealthcareTransactionreporting• Evidence-based medicine• Personalized healthcare• Dynamic fraud detection• Patient, member behavior• Enterprise-wide data• Enterprise analytics• Clinical outcomes reporting• Unified data sources• Clinical data repositories• Departmental data marts• Dashboards• Spreadsheets• Separate data sources• Manual collation of data• Basic reportingData integrationData warehouseClinicalanalyticsAdvancedanalytics• What are the main predictors for readmission?• What patients are most at risk for a bad outcome?• What patients require intervention for me to provide best care?• What care programs lead to the best outcome for this patient?
  • 9. So How many of these guys do you need to runyour analytics program?
  • 10. Organizational issues cited as key barriers toanalytics adoptionPrimary obstacles to widespread analytics adoptionOrganizationalDataFinancialSource: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © MassachusettsInstitute of Technology 2010. Sample size Healthcare n= 116Lack of understanding how to useanalytics to improve the business 34%Lack of management bandwidth due tocompeting priorities25%Lack of skills internally in the line ofbusiness23%Ability to get the data 37%Ownership of the data is unclear orgovernance is ineffective 17%Concerns with the data 3%Perceived costs outweigh the projectedbenefits9%No case for change 19%Don’t know where to start 17%Lack of executive sponsorship 24%Culture does not encourage sharing information 35%
  • 11. Business UsersDefine what they want to analyzeIT Builds solutionsTraditional ModelIT Creates Big Data PlatformBig Data ModelExploratory Analysis
  • 12. How does this change your enterprise dataarchitecture?
  • 13. © 2012 IBM Corporation15•Workload optimized relationalsystems•SSOT, Operational, Analytic•10-100’s of TB of data•High Performance and thruputOperationalDatabasesAnalyticalData MartsData WarehouseExecs, CategoryManagers, BuyersAnalysts, Data Scientists,Analytic AppsDigitalCRMPharmacySupplyChainCallCenterSource systemsFinanceEvolutionary Phase I
  • 14. © 2012 IBM Corporation16OperationalDatabasesAnalyticalData MartsData WarehouseExecs, CategoryManagers, BuyersAnalysts, Data Scientists,Analytic AppsSocialUnstructuredSourcesMobileAppsTwitterHadoop• Unstructured data processing• QueryableArchive• Analytics Sandbox• Low cost storageDigitalCRMPharmacySupplyChainCallCenterSource systemsFinanceEvolutionary Phase II
  • 15. © 2012 IBM Corporation17OperationalDatabasesAnalyticalData MartsData WarehouseSocialExternalSourcesMobileAppsTwitterReal Time Decisioning•Low latency analtyics•Analyze data “in-motion”•In-memory, Complex events•Scale out modelDigitalCRMPharmacySupplyChainCallCenterSource systemsFinanceEvolutionary Phase III
  • 16. © 2012 IBM Corporation18SocialExternalSourcesCustomAppsTwitterBig Data PlatformSystemsManagementApplicationDevelopmentVisualization& DiscoveryAnalytic AcceleratorsInformation Integration & GovernanceBI /ReportingExploration /VisualizationFunctionalAppIndustryAppPredictiveAnalyticsContentAnalyticsAnalytic Applications• Integration• Visualization• Development• Security• GovernanceHadoopSystemStreamComputingDataWarehouseDigitalCRMPharmacySupplyChainCallCenterSource systemsFinance
  • 17. Big Data Challenges Have Diverse RequirementsManage and analyzeunstructured data3Hadoop File System / MapReduceText AnalyticsAnalyze data in real time4 Stream ComputingDiscover, explore andnavigate big data sourcesFederated Discovery, Search and Navigation1Extreme Performance –run analytics closer to data2Massively Parallel ProcessingAnalytic EnginesRich library of analyticalfunctions and tools5In-Database Analytics LibrariesBig Data visualizationIntegrate and govern alldata sources6Integration, DataQuality, Security, LifecycleManagement, MDM
  • 18. Each of these Use Cases Combine MultipleTechnologiesPre-processingIngest and analyze unstructured data typesand convert to structured dataCombine structured and unstructured analysisAugment data warehouse with additional externalsources, such as social mediaCombine high velocity and historical analysisAnalyze and react to data in motion; adjust modelswith deep historical analysisReuse structured data for exploratory analysisExperimentation and ad-hoc analysis with structureddata
  • 19. Big data adoptionWhen segmented into four groups based on current levels of big data activity, respondents showed significant consistency inorganizational behaviors Total respondents n = 1061Totals do not equal 100% due to roundingOrganizations are adopting big data in phases
  • 20. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureThe IBM Big Data Platform
  • 21. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureDelivers deep insightwith advanced in-database analytics &operational analytics PureData forAnalytics – expertintegrated systems tomake advancedanalytics faster&simplerDataWarehouseDataWarehouseThe IBM Big Data Platform
  • 22. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureStreamComputingDataWarehouseAnalyze streaming dataand large data burstsfor real-time insights InfoSphere Streams– software enablingcontinuous analysis ofmassive volumes ofstreaming data withsub-millisecondresponse timesStreamComputingThe IBM Big Data Platform
  • 23. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureHadoopSystemStreamComputingDataWarehouseCost-effectively analyzePetabytes ofunstructured andstructured data InfoSphereBigInsights --enterprise-gradeHadoop systemenhanced withadvanced textanalytics, datavisualization, tools, &performance featuresfor analyzing massivevolumes of structuredand unstructureddata.HadoopSystemThe IBM Big Data Platform
  • 24. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureInformation Integration & GovernanceHadoopSystemStreamComputingDataWarehouseGovern data quality andmanage the informationlifecycle InfoSphere InformationServer –Cleanses data,monitors quality andintegrates big data withexisting systems InfoSphere Optim –manages businessinformation throughout itslifecycle InfoSphere MasterData Management –manages and maintainstrusted views of masterand reference data InfoSphere Guardium–real-time databasesecurity and monitoringInformation Integration & GovernanceThe IBM Big Data Platform
  • 25. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureAcceleratorsInformation Integration & GovernanceHadoopSystemStreamComputingDataWarehouseSpeed time to valuewith analytic andapplication accelerators AnalyticAccelerators – textanalytics, geospatial,time-series, datamining ApplicationAccelerators –financial services,machine data, socialdata, Telco event data Industry Models- comprehensive datamodels based ondeep expertise andindustry best practiceAcceleratorsThe IBM Big Data Platform
  • 26. SolutionsIBM Big Data PlatformAnalytics and Decision ManagementBig Data InfrastructureAcceleratorsInformation Integration & GovernanceHadoopSystemStreamComputingDataWarehouseSystemsManagementApplicationDevelopmentVisualization& DiscoveryDiscover, understand,search, and navigatefederated sources ofbig data InfoSphere DataExplorer – Discoveryand navigationsoftware that providesreal-time access andfusion of big data withrich and varied datafrom enterpriseapplications forgreater insightVisualization& DiscoveryThe IBM Big Data Platform