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Use cases for Hadoop and Big Data Analytics - InfoSphere BigInsights

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This presentation is from TDWI's event in Boston during the summer of 2014. IBM InfoSphere BigInsights is IBM's enterprise grade Hadoop offering. It combines the best of open-source Hadoop, with advanced capabilities including Big SQL that clients can optionally deploy to get to market faster with a variety of big data and analytic applications.

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Use cases for Hadoop and Big Data Analytics - InfoSphere BigInsights

  1. 1. © 2014 IBM Corporation Getting Started with Big Data Five Game Changing use cases Gord Sissons IBM InfoSphere BigInsights
  2. 2. © 2014 IBM Corporation2 annual Internet traffic by 2016 Internet of Information e-mails per minute Internet of Engagement users of social media today by 2017 Internet of Things connected devices today by 2020 Big Data is every where we look
  3. 3. © 2014 IBM Corporation3 Driven by new technological capabilities and transformative economics • Vertical infrastructure for DW/BI • What data should I keep? • Design schemas in advance • ETL, down-sample, aggregate • What reports do I need? The Old Way The New Way • Distributed data grids • Keep everything just in case • Evolve schemas on the fly • Extract knowledge from raw data directly • Test every theory, model “what- ifs” on the fly A new way of thinking
  4. 4. © 2014 IBM Corporation4 Big Data Objectives Customer-centric outcomes Operational optimizations Risk / financial management New business model Employee collaboration 49% 4% 18% 15% 14% Customer-centric outcomes Other objectives Total respondents n = 1061 Top functional objectives identified by organizations with active big data pilots or implementations. Responses have been weighted and aggregated. - http://www-935.ibm.com/services/us/gbs/thoughtleadership/ninelevers/
  5. 5. © 2014 IBM Corporation5 Data Warehouse Modernization Integrate big data and data warehouse capabilities to increase operational efficiency Operations Analysis Analyze a variety of machine data for improved business results Big Data Exploration Find, visualize, understand all big data to improve business knowledge Enhanced 360o View of the Customer Achieve a unified view, incorporating many data sources Security/Intelligence Extension Lower risk, detect fraud and monitor security in real-time Five Big Data use cases
  6. 6. © 2014 IBM Corporation6 66 City of Dublin; City-wide traffic awareness system, enhance incident response Need • A cost effective solution to improve traffic awareness system • Accuracy in event detection, inferring traffic conditions and predicting bus arrival times • Challenge is to correctly analyze GPS data - high throughput, difficult to capture Benefits • Monitor 1000 busses across 150 routes daily • Analyzes 50 bus location updates per second • Collects, processes, and visualizes location data of all public transportation vehicles 6 Operations Analysis http://www-03.ibm.com/press/us/en/pressrelease/41068.wss
  7. 7. © 2014 IBM Corporation7 Campaign launch time 80% reduction Campaign performance driving ROI 70% improvement Reduction in analytic processing time 90% reduction Reduced churn through personalized loyalty campaigns, increased ARPU Celcom Axiata Enhanced 360 view of the customer http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=C192500J38882P30
  8. 8. © 2014 IBM Corporation8 © 2013 IBM Corporation Increases knowledge worker efficiency saving USD36 million per year in one department alone.  80,000 internal users, 40,000+ external users  Accessing dozens of separate data sources throughout the enterprise  Single-point of data fusion for all employees  Improved operational performance for multiple departments  50 additional aircraft in service with no staffing increase Global Aerospace Manufacturer Big Data Exploration http://www.airbus.com/presscentre/pressreleases/press-release- detail/detail/airbus-and-ibm-to-help-aircraft-operators-optimize- fleet-management-and-operations/
  9. 9. © 2014 IBM Corporation9 Major energy company uses stream data to monitor ice- flow movement in real time Need • Acquire streaming data from a variety of sources to analyze atmospheric conditions • Thousands of data points per second • Analyze massive volumes of data continuously at rates up to petabytes per day • Adapt to rapidly changing data forms and types • Leverage sub-millisecond latencies to respond to events and trends as they unfold Benefits • Anticipates saving roughly USD 300 million per season by reducing mobilization costs associated with needing to drill a second well • Estimates savings of USD 1 billion per production platform by easing design requirements, optimizing rig replacement and improving ice management operations 9 Operations Analysis http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=C192500J38882P30
  10. 10. © 2014 IBM Corporation10 Analyzed behavior patterns 25% increase in email opening rate Improved wait times Data analysis performance increased by 40x Reduced IT workload ETL development resources reduced by 50% Constant Contact Data Warehouse Modernization http://www.ibmbigdatahub.com/video/ibm-big-data-solutions-redefining-e-mail-marketing-success-constant-contact
  11. 11. © 2014 IBM Corporation11 Time to value matters Just because you can build a solution from scratch doesn’t mean you should!
  12. 12. © 2014 IBM Corporation12 Information Integration & Governance Systems Security On premise, Cloud, As a service Storage New/Enhanced Applications All Data What action should I take? Decision management Cognitive Fabric Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone Data Warehouse Modernization
  13. 13. © 2014 IBM Corporation13 IBM InfoSphere® BigInsights  100% standard Hadoop  Extensive capability  BigSheets, Big SQL, Big R  Pre-built Accelerators  Streaming Analytics  Breakthrough performance  POSIX file system  Extensive solution ecosystem Compressed time to business value
  14. 14. © 2014 IBM Corporation14 Learning more http://BigDataUniversity.COM http://BigDataHub.COM
  15. 15. © 2014 IBM Corporation15 Learning more http://Developer.IBM.COM/Hadoop http://Developer.IBM.COM/Streams
  16. 16. © 2014 IBM Corporation16 Thank you! @GJSissons gsissons@ca.ibm.com
  17. 17. © 2014 IBM Corporation17 For Discussion What are the critical success factors associated with ensuring that a big data or analytics initiative delivers a successful business outcome?
  18. 18. © 2014 IBM Corporation18 IBM’s Research Analytics: a blueprint for value. Converting big data and analytics insights into results http://www.ibm.com/services/us/gbs/ thoughtleadership/ninelevers/

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