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The Big Data Market


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The Big Data Market

  1. 1. © 2013 IBM Corporation The Big Data Market
  2. 2. © 2014 IBM Corporation2 45 49 80 86 39 41 78 92 0 50 100 150 200 250 300 2015 2017 MarketOpportunity($B) Big Data&Analytics Served(Measured) Opportunity GTS GBS SWG STG “A planet of data – Today, every discussion about changes in technology, business and society must begin with data” – Ginni Rometty (2014) NEW IT ECONOMICS NEW SOURCES OF DATA NEW BUYERS, NEW USERS, NEW WAYS OF WORKING NEW ACTIONABLE INSIGHTS • Digitization of everything and growth of content • Instrumentation, Internet of Things • Multiple data sources (structured, unstructured) Transformational Market Drivers • Cloud & Open Source • In-memory computing • Solid-state drives / Flash memory • Accelerating storage and compute capacity • Real-time contextual insight with action • Enhanced 360 degree view of everything • Industry domain focus • Increasing LOB purchasing influence • Consumable solutions for business users • Emerging skill classes (e.g. data scientists, domain experts, Chief Data Officers) $242 $268 Total combined opportunity of $270M by 2017 across Software, Hardware, and Services
  3. 3. © 2014 IBM Corporation3 North America is the largest opportunity while GMU has strongest growth Source: BAOPivot1H13, BAO opportunity based on MI Modeled 1H13 estimates and 2Q12 Strategic Solutions estimates
  4. 4. © 2014 IBM Corporation4 0 5,000 10,000 15,000 20,000 25,000 Telecommunications Banking Wholesale & CPG Central Government Industrial Products Electronics Local Government Insurance Retail CSI Media & Entertainment Energy & Utilities Financial Markets Automotive Transportation Health Provider Life Sciences Petroleum Travel Higher Education Chemical Aerospace & Defense Education(K-12) Health Payor Top six industries account for nearly 50% of both existing and growth opportunity to 2015 50% BD&A Market Opportunity ($M) Key: Blue: 2012 Green: growth to 2015 Source: BAOPivot1H13, BAO opportunity based on MI Modeled 1H13 estimates and 2Q12 Strategic Solutions estimates
  5. 5. © 2014 IBM Corporation5 Sources: Business Wire: SAS Survey Signals Big Data Disconnect: only 12% Onboard; Big Data Analytics, TDWI Research 4Q2011 Only a few organizations are currently executing against a big data strategy in daily operations, despite the competitive advantage it offers Reasons for Not Exploiting Big Data 1.21% Don’t know enough about big data 2.15% don’t understand the benefits 3. 9% lack business support 4. 9% lack data quality in existing systems IDC estimates that 41% of clients are not sure how to measure the value of analytics Only 28% of companies have a Big data business plan with measurable goals Business Data Case: 1.With Proven ROI 14% 2.With projected ROI 14% 3.With intangible benefits only 15% 4.No case, but working on one 14% 5.Planning one in next 12 months 15% 6.No explicit business case 28% Source: Forrsights BI/Big Data Survey, Q3 2012 Base: 176 Big Data users and planners
  6. 6. © 2014 IBM Corporation6 Big Data and Analytics initiatives are being driven by LOB, more so than IT, with Marketing/Sales and BPO benefiting so far The Big Data initiative is primarily driven by: Source: Talend: “How big is Big Data adoption?”, Summer 2012 To date, have you realized any business benefits to Big Data? N = 231 data professionals N = 95 data professionals
  7. 7. © 2014 IBM Corporation77 CEO CIO CMOCFO • Respond to the market • Understand the customer • Collaborate internally • Drive insight & intelligence • Partner to innovate Leaders across the C-Suite are seeking assistance from Big Data & Analytics to help them manage costs and risk while driving growth • Handle market complexity • Harness the power of the data explosion through analytics • Capture & leverage unstructured data, including social data • Enhance customer loyalty & advocacy • Reduce costs • Define KPI’s • Manage risk • Consolidate & integrate infrastructure • Drive better decisions with analytics • Manage security & compliance • Manage IT costs • Leverage IT to grow business, incl. new products & customers Source: IBM CEO,CIO, CFO, CMO Studies 7 Source: 2H12 IM MPA, IBM MD&I, synthesis of primary and secondary research
  8. 8. © 2014 IBM Corporation88 • Cut costs, improve efficiencies • Improve security, transparency, public participation, and internal collaboration • Analyze and predict events related to security, reduce fraud and better serve population • Manage proliferation of of text and numerical data including customer data & transaction information • Optimize marketing spend, increase ROI • Optimize inventory & supply chain • Manage high volumes of customer data being driven by operational systems • Protect revenue and reduce customer churn • Deliver value add services by having 'single view' of customer and their changing behavior • Optimize mobile data and network efficiency • Consolidate data and datacenter • Automate patient records & vendor payments • Implement electronic health records • Innovate - study the human genome • Map the clinical value chain in an integrated solution • Manage risk & detect fraud • Manage explosive growth in trade volumes and shrinking trade size • Increase customer focus for the business • Reduce data management costs • Optimize supply chain • Synchronize data with suppliers for sourced products and retailers for sales • Create centralized view of product and parts data for inventory control • Reduce production downtime • Improve processing speed of new applications • Reduce inconsistencies in the increased manual claims processing • Customize sales campaigns by improving claims segmentation • Forecast /plan shutdowns • Improve utilization of assets, reduce outages • Improve integration of energy management systems To be effective, you must be able to discuss the industry-specific needs and pain points of business leaders Gov’t Retail Telco Medical Banking Manufact. Insurance Utilities Industry-Specific Pain Points Source: 2H12 IM MPA, IBM MD&I, synthesis of primary and secondary research 8
  9. 9. © 2014 IBM Corporation9 Where are we with Big Data & Analytics in 2014?
  10. 10. © 2014 IBM Corporation10 30% Reduction in heating bills The Opportunities from Big Data & Analytics Are Infinite 15 min Response time to requests 150% Revenue growth rate 95%Accuracy of 18+ month sales forecasts 80% Less time required to open an account 98.5% On-time delivery target achieved 70%Counterparty measurements changed 80%Reduction in serious accidents Every Industry can Leverage Big Data and Analytics
  11. 11. © 2014 IBM Corporation11 Paradigm shifts enabled by big data Leverage more of the data being captured TRADITIONAL APPROACH BIG DATA APPROACH Analyze small subsets of information Analyze all information Analyzed information All available information All available information analyzed
  12. 12. © 2014 IBM Corporation12 Paradigm shifts enabled by big data Reduce effort required to leverage data TRADITIONAL APPROACH BIG DATA APPROACH Carefully cleanse information before any analysis Analyze information as is, cleanse as needed Small amount of carefully organized information Large amount of messy information
  13. 13. © 2014 IBM Corporation13 Paradigm shifts enabled by big data Data leads the way—and sometimes correlations are good enough TRADITIONAL APPROACH BIG DATA APPROACH Start with hypothesis and test against selected data Explore all data and identify correlations Hypothesis Question DataAnswer Data Exploration CorrelationInsight
  14. 14. © 2014 IBM Corporation14 Paradigm shifts enabled by big data Leverage data as it is captured TRADITIONAL APPROACH BIG DATA APPROACH Analyze data after it’s been processed and landed in a warehouse or mart Analyze data in motion as it’s generated, in real-time Repository InsightAnalysisData Data Insight Analysis
  15. 15. © 2014 IBM Corporation15 Actionable insight Data Marts Data types Transaction and application data Predictive analytics and modeling Reporting and analysis Operational systems Archive Enterprise Warehouse Staging area Traditional enterprise data and analytics environments
  16. 16. © 2014 IBM Corporation16 Where are we going with Big Data ?
  17. 17. © 2014 IBM Corporation17 Watson Foundations 1 2 4 3 3 3 3 3 5 1 2 3 4 5 More Than Hadoop Greater resiliency and recoverability Advanced workload management & multi-tenancy Enhanced, flexible storage management (GPFS) Enhanced data access (BigSQL, Search) Analytics accelerators & visualization Enterprise-ready security framework Data In Motion Enterprise class stream processing & analytics Analytics Everywhere Richest set of analytics capabilities Ability to analyze data in place Governance Everywhere Complete integration & governance capabilities Ability to govern all data where ever it is Complete Portfolio End-to-end capabilities to address all needs Ability to grow and address future needs 3 3 Next generation architecture for delivering information and insights
  18. 18. © 2014 IBM Corporation18