Big Data Forum - Phoenix
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The document discusses the IBM Big Data Forum held on May 16, 2013, focusing on the significance of big data and analytics as tools for achieving competitive advantage. It outlines various use cases across sectors such as healthcare and retail, highlights organizational challenges to adopting analytics, and describes IBM's big data solutions and platforms. Additionally, it emphasizes the importance of integrating structured and unstructured data and the evolution of enterprise data architecture to support advanced analytics.
Big Data Forum - Phoenix
- 1. IBM Big Data Forum Salt River Fields, Phoenix, Arizona 16 May 2013 Krishnan Parasuraman
- 2. Talking Points What is Big Data?1 What is the relationship between Big Data and Analytics? 2 What does a Big Data Platform look like?3 What are the different entry points into Big Data?4 What is IBM’s strategy in Big Data?5
- 3. The number of organizations who see analytics as a competitive advantage is growing. 2010 2011 2012 63%
- 4. IBM IBV/MIT Sloan Management Review Study 2011 Copyright Massachusetts Institute of Technology 2011 Studies show that organizations competing on analytics substantially outperform their peers 1.6xRevenue Growth 2.0x EBITDA Growth2.5x Stock Price Appreciation 4
- 5. Analytics (by itself) = Blah. Analytics + Big Data = Kickass Competitive Advantage
- 6. Big Data Analytics Use Cases Call Centers Voice-to-text mining for understanding customer sentiment Healthcare Genomics Analytics Medical Record Analytics E Commerce / Retail Clickstream analytics Analyze online behavior and buying patterns Oil and Gas / Energy Geospatial Analysis Windmill placements
- 7. The Analytics Continuum…in Healthcare Transaction reporting • 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 reporting Data integration Data warehouse Clinical analytics Advanced analytics • 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 Healthcare Transaction reporting • 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 reporting Data integration Data warehouse Clinical analytics Advanced analytics • 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?
- 11. So How many of these guys do you need to run your analytics program?
- 12. Organizational issues cited as key barriers to analytics adoption Primary obstacles to widespread analytics adoption Organizational Data Financial Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010. Sample size Healthcare n= 116 Lack of understanding how to use analytics to improve the business 34% Lack of management bandwidth due to competing priorities 25% Lack of skills internally in the line of business 23% Ability to get the data 37% Ownership of the data is unclear or governance is ineffective 17% Concerns with the data 3% Perceived costs outweigh the projected benefits 9% No case for change 19% Don’t know where to start 17% Lack of executive sponsorship 24% Culture does not encourage sharing information 35%
- 13. Business Users Define what they want to analyze IT Builds solutions Traditional Model IT Creates Big Data Platform Big Data Model Exploratory Analysis
- 14. How does this change your enterprise data architecture?
- 15. © 2012 IBM Corporation15 •Workload optimized relational systems •SSOT, Operational, Analytic •10-100’s of TB of data •High Performance and thruput Operational Databases Analytical Data Marts Data Warehouse Execs, Category Managers, Buyers Analysts, Data Scientists, Analytic Apps Digital CRM Pharmacy Supply Chain Call Center Source systems Finance Evolutionary Phase I
- 16. © 2012 IBM Corporation16 Operational Databases Analytical Data Marts Data Warehouse Execs, Category Managers, Buyers Analysts, Data Scientists, Analytic Apps Social Unstructured Sources Mobile Apps Twitter Hadoop • Unstructured data processing • QueryableArchive • Analytics Sandbox • Low cost storage Digital CRM Pharmacy Supply Chain Call Center Source systems Finance Evolutionary Phase II
- 17. © 2012 IBM Corporation17 Operational Databases Analytical Data Marts Data Warehouse Social External Sources Mobile Apps Twitter Real Time Decisioning •Low latency analtyics •Analyze data “in-motion” •In-memory, Complex events •Scale out model Digital CRM Pharmacy Supply Chain Call Center Source systems Finance Evolutionary Phase III
- 18. © 2012 IBM Corporation18 Social External Sources Custom Apps Twitter Big Data Platform Systems Management Application Development Visualization & Discovery Analytic Accelerators Information Integration & Governance BI / Reporting Exploration / Visualization Functional App Industry App Predictive Analytics Content Analytics Analytic Applications • Integration • Visualization • Development • Security • Governance Hadoop System Stream Computing Data Warehouse Digital CRM Pharmacy Supply Chain Call Center Source systems Finance
- 19. Big Data Challenges Have Diverse Requirements Manage and analyze unstructured data3 Hadoop File System / MapReduce Text Analytics Analyze data in real time4 Stream Computing Discover, explore and navigate big data sources Federated Discovery, Search and Navigation1 Extreme Performance – run analytics closer to data2 Massively Parallel Processing Analytic Engines Rich library of analytical functions and tools5 In-Database Analytics Libraries Big Data visualization Integrate and govern all data sources 6 Integration, Data Quality, Security, Lifecycle Management, MDM
- 20. Each of these Use Cases Combine Multiple Technologies Pre-processing Ingest and analyze unstructured data types and convert to structured data Combine structured and unstructured analysis Augment data warehouse with additional external sources, such as social media Combine high velocity and historical analysis Analyze and react to data in motion; adjust models with deep historical analysis Reuse structured data for exploratory analysis Experimentation and ad-hoc analysis with structured data
- 21. Big data adoption When segmented into four groups based on current levels of big data activity, respondents showed significant consistency in organizational behaviors Total respondents n = 1061 Totals do not equal 100% due to rounding Organizations are adopting big data in phases
- 22. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure The IBM Big Data Platform
- 23. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure Delivers deep insight with advanced in- database analytics & operational analytics PureData for Analytics – expert integrated systems to make advanced analytics faster &simpler Data Warehouse Data Warehouse The IBM Big Data Platform
- 24. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure Stream Computing Data Warehouse Analyze streaming data and large data bursts for real-time insights InfoSphere Streams – software enabling continuous analysis of massive volumes of streaming data with sub-millisecond response times Stream Computing The IBM Big Data Platform
- 25. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure Hadoop System Stream Computing Data Warehouse Cost-effectively analyze Petabytes of unstructured and structured data InfoSphere BigInsights -- enterprise-grade Hadoop system enhanced with advanced text analytics, data visualization, tools, & performance features for analyzing massive volumes of structured and unstructured data. Hadoop System The IBM Big Data Platform
- 26. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure Information Integration & Governance Hadoop System Stream Computing Data Warehouse Govern data quality and manage the information lifecycle InfoSphere Information Server –Cleanses data, monitors quality and integrates big data with existing systems InfoSphere Optim – manages business information throughout its lifecycle InfoSphere Master Data Management – manages and maintains trusted views of master and reference data InfoSphere Guardium– real-time database security and monitoring Information Integration & Governance The IBM Big Data Platform
- 27. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure Accelerators Information Integration & Governance Hadoop System Stream Computing Data Warehouse Speed time to value with analytic and application accelerators Analytic Accelerators – text analytics, geospatial, time-series, data mining Application Accelerators – financial services, machine data, social data, Telco event data Industry Models - comprehensive data models based on deep expertise and industry best practice Accelerators The IBM Big Data Platform
- 28. Solutions IBM Big Data Platform Analytics and Decision Management Big Data Infrastructure Accelerators Information Integration & Governance Hadoop System Stream Computing Data Warehouse Systems Management Application Development Visualization & Discovery Discover, understand, search, and navigate federated sources of big data InfoSphere Data Explorer – Discovery and navigation software that provides real-time access and fusion of big data with rich and varied data from enterprise applications for greater insight Visualization & Discovery The IBM Big Data Platform