IBM Software Day 2013. Smarter analytics and big data. building the next generation of analytical insights


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IBM Software Day 2013. Smarter analytics and big data. building the next generation of analytical insights

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IBM Software Day 2013. Smarter analytics and big data. building the next generation of analytical insights

  1. 1. Smarter Analytics and Big DataBuilding The Next GenerationAnalytical insightsJoel WatermanRegional Director, Business Analytics Middle East & Africa
  3. 3. O’Reilly:27.4.2011, Got Iphone, Apple is recording your moves
  4. 4. TomTom Caught Selling Speed Data to Dutch Police PcWorld 28. April 2011
  5. 5. Why Business Analytics MatterEight out of ten CEOs expect complexity to Enterprises that apply advanced analyticsincrease significantly in the next five years; have 33% more revenue growth and 12Xinsight and intelligence is ranked a top 3 more profit growth.priority. - CEO study 2010 – CFO study 2010Financial outperformers are 64% more likely CIOs rank analytics as the #1 factorto use analytics to evaluate talent supply and contributing to an organization’sdemand on an ongoing basis. competitiveness. – CHRO study 2010 – CIO study 2009Top-performing enterprises use business analytics 5 times more than lower performers. – 2010 joint study, MIT and IBM Institute for Business Value
  6. 6. Why Business Analytics MatterThe Need for Analytics is Pervasive Across Business and Industry The healthcare industry spends $250 - $300 billion on healthcare fraud, per year. In the US alone this is a $650 million per day problem.1 One rogue trader at a leading global financial services firm created $2 billion worth of losses, almost bankrupting the company. $93 billion in total sales is missed each year because retailers don’t have the right products in stock to meet customer demand. 5 billion global subscribers in the telco industry are demanding unique and personalized offerings that match their individual lifestyles. 2 Source: 1. Harvard, Harvard Business Review, April 2010. 2. IBM Institute for Business Value, The Global CFO Study, 2010.
  7. 7. IBM is Making Significant Investments in Smarter Analytics Investment  $ 16B for 30 acquisitions since 2005  8 Analytic Solutions Centers worldwideTechnical Expertise  More than 10,000 technical professionals  9,000 consultants delivering IBM analytics solutions  Power7: workload optimized analytic processing Technology  Smart Analytics cloud  Comprehensive, heterogeneous Big Data platform for the Enterprise  World’s largest math department in private industry  FOAK breakthrough innovations including IBM Watson Research  Number 1 in patent ranking for 19 years and more than 500 analytics-related patents / year for last two yearsBusiness Partners  More than 27,000 Business Partner certifications
  8. 8. Imagine the Possibilities of Analyzing All Available Data Faster, More Comprehensive, Less Expensive Real-time Traffic Fraud & risk Understand and act onFlow Optimization detection customer sentimentAccurate and timely Predict and act on Low-latency network threat detection intent to purchase analysis
  9. 9. Cisco turns to IBM big data for intelligent infrastructure management• Optimize building energy consumption with centralized monitoring• Automate preventive and corrective maintenanceCapabilities Utilized: • Streaming Analytics • Hadoop System • Business IntelligenceApplications: • Log Analytics • Energy Bill Forecasting • Energy consumption optimization • Detection of anomalous usage • Presence-aware energy mgt. • Policy enforcement
  10. 10. Harnessing the Largest Predictive Focus Group in the WorldPurpose • Understand public sentiment towards an event: movie trailers • Deeply understand the potential customer profile: gender, occupation, intent to watch • Alter marketing launch plans based on insightBackground • 1.1 Billion Tweets analyzed • 5.7 Million blogs/forum posts • 3.5 million messages • Also: Facebook, Google+, Tumblr, Flickr
  11. 11. Conclusion – Actionable InsightAdjust the marketing launch plan beforeexecution begins• Creative – adjust messaging• Trailers – alter scenes shown• Budget – re-direct, increase, or decrease• Execution – theatre placement, advertisement placement
  12. 12. IBM Big Data Platform
  13. 13. IBM Big Data Strategy: Move the Analytics Closer to the Data Analytic ApplicationsNew analytic applications drive the BI /Reporting Exploration / Visualization Functional App Industry App Predictive Analytics Content Analyticsrequirements for a big data platform IBM Big Data Platform • Visualize all available data for ad-hoc Visualization Application Systems analysis & Discovery Development Management • Development environment for building new analytic applications Accelerators • And a whole lot good solid IT stuff... Hadoop Stream Data System Computing Warehouse Information Integration & Governance
  14. 14. Big Data Platform - Hadoop System• Manages a wide variety and huge volume of data• Augments open source Hadoop with enterprise capabilities • Performance Optimization • Development tooling • Enterprise integration • Analytic Accelerators • Application and industry accelerators • Visualization • Security
  15. 15. DC WATER
  16. 16. IBM’s Hadoop System provides unique business value• Integration with enterprise systems• Industry & application accelerators• Templates for quick starting app dev• Visualization tools to help business users to explore big data
  17. 17. Big Data Platform - Stream Computing Built to analyze data in motion• Multiple concurrent input streams • Massive scalability Process and analyze a variety of data • Structured, unstructured content, video, audio • Advanced analytic operators
  18. 18. Asian telco reducesbilling costs and improvescustomer satisfactionCapabilities: Stream Computing Analytic AcceleratorsReal-time mediation and analysis of 6B CDRs per dayData processing time reduced from 12 hrs to 1 secHardware cost reduced to 1/8thProactively address issues (e.g. dropped calls) impacting customer satisfaction.
  19. 19. Stream Computing provides unique business value• Real-time answers = Better outcomes for time sensitive applications (e.g. fraud detection, network management)• Solution when data is too large or expensive to store • Analyze data as it comes to you • Keep data of interest for deeper analysis
  20. 20. Big Data Platform - Data Warehousing Workload optimized systems • Deep analytics appliance • Configurable operational analytics appliance • Data warehousing software Capabilities • Massive parallel processing engine • High performance (OLAP) • Mixed operational and analytic workloads
  21. 21. Deep Analytics Appliance – Revolutionizing AnalyticsPurpose-built analytics appliance Dedicated High Performance Disk StorageSpeed: 10-100x faster than traditional systemsSimplicity: Minimal administration and tuningScalability: Peta-scale user data capacitySmart: High-performance advanced analytics Blades With Custom FPGA Accelerators
  22. 22. Pacific Northwest Smart GridDemonstration ProjectCapabilities: Stream Computing – real-time control system Deep Analytics Appliance – analyze massive data setsDemonstrates scalability from 100 to500K homes while retaining 10 years’historical data60k metered customers in 5 statesAccommodates ad hoc analysis of pricefluctuation, energy consumption profiles,risk, fraud detection, grid health, etc.
  23. 23. Data Warehousing provides unique business value• Consolidate, manage and reconcile data for enterprise business intelligence• Establish trust, quality and governance where necessary • Financial data • Credit card data • Healthcare• Combine deep and operational analytics• Maintain history for trending and historical reporting Image: David Castillo Dominici
  24. 24. Big Data Platform - Accelerators Analytic accelerators • Analytics, operators, rule sets Industry and Horizontal Application Accelerators • Analytics • Models • Visualization / user interfaces • Adapters
  25. 25. Analytic Accelerators Designed for Variety Text (listen, verb), Simple & Acoustic (radio, noun) Advanced Text Mining in Advanced Microseconds Mathematical Models Predictive ∑R( s , a ) population t t Statistics GeoSpatial Image & Video
  26. 26. Accelerators Improve Time to Value Telecommunications Retail Customer CDR streaming analytics Intelligence Deep Network Analytics Customer Behavior and Lifetime Value Analysis Finance Social Media Analytics Streaming options trading Sentiment Analytics, Intent to purchase Insurance and banking DW models Public transportation Data mining Real-time monitoring and Streaming statistical analysis routing optimizationOver 100 sample User Defined Toolkits Standard Toolkits Industry Data Modelsapplications Banking, Insurance, Telco, Healthcare, Retail
  27. 27. Telecommunications CDR Analytic AcceleratorAnalyze Call Detail Records in real timeStreaming Analytic Accelerators • Dropped call analysis • Who are VIP customers with service issues – proactive alerts • Analytic Operators – CDR de-duplication, dropped call detection, termination reason, customer importance • Visualization – real-time KPI dashboardData Warehouse Appliance • Integrated network, devices, customer, and services model • Telecom model, KPIs, and KQIs Image: nokhoog_buchachon
  28. 28. Big Data Platform – Information Integration and Governance  Integrate any type of data to the big data platform • Structured • Unstructured • Streaming  Govern big data • Secure sensitive data • Lifecycle management to control data growth • Master data to establish single version of the truth
  29. 29. Information and Governance for Big Data
  30. 30. Marketing Services Leader integrates big data forLeaders integrate and govern massive Big Data with InfoSphere customer intelligenceCapabilities Utilized: Information Integration – data quality, ETL Deep Analytics ApplianceComplex customer data integration for 54M records/hour Processing 5B simultaneous records32 Manages32 2 petabytes of data,
  31. 31. Big Data Platform - User InterfacesBusiness Users•Visualization of a large volume and wide variety of dataDevelopers • Similarity in tooling and languages • Mature open source tools with enterprise capabilities • Integration among environmentsAdministrators • Consoles to aid in systems management
  32. 32. Visualization - Spreadsheet-style user interface • Ad-hoc analytics for LOB user • Analyze a variety of data - unstructured and structured • Browser-based • Spreadsheet metaphor for exploring/ visualizing data Gather Extract Explore IterateCrawl – gather statistically Document-level info Analyze, annotate, filter Iterate through any priorAdapter–gather Cleanse, normalize Visualize results stepdynamically
  33. 33. Big Data Platform - Analytic ApplicationsBig Data Platform is designed for analyticapplication development and integrationBI/Reporting – Cognos BI, AttivioPredictive Analytics – SPSS, G2, SASExploration/Visualization – BigSheets, DatameerInstrumentation Analytics – Brocade, IBM GBS ContentAnalytics – IBM Content AnalyticsFunctional Applications – Algorithmics, Cognos ConsumerInsights, Clickfox, i2, IBM GBSIndustry Applications – TerraEchos, Cisco, IBM GBS
  34. 34. IBM’s big data business partner ecosystem 100thCC&G Partners Big Data Business Partner Signed
  35. 35. IBM’s unique strengths in Big Data Big Data in Real-Time Fit for purpose analytics Enterprise Class Integration
  36. 36.  WATCH A MOVIE
  37. 37.  DOWNLOAD AN APP visit and download the IBM Institute for Business Value app at iTunes and Android Marketplace
  38. 38.  READ A PAPER