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Big Data & Analytics – beyond Hadoop

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Big Data & Analytics – beyond Hadoop

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Ian Radmore, an IBM Big Data Specialist spoke about the velocity aspect of the 4Vs associated with Big Data at the recent Internet World conference, this is the supporting presentation.

Ian Radmore, an IBM Big Data Specialist spoke about the velocity aspect of the 4Vs associated with Big Data at the recent Internet World conference, this is the supporting presentation.

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Big Data & Analytics – beyond Hadoop

  1. 1. © 2014 IBM Corporation Big Data & Analytics – beyond Hadoop Ian Radmore, IBM UKI Big Data Specialist June 18th, 2014
  2. 2. © 2014 IBM Corporation Data: To have and to hold? Or to Analyse and Act! Data in Data at 2
  3. 3. © 2014 IBM Corporation The auto industry is already the 2nd largest data generator AND 20% CAGR! Ford Fusion: 145 actuators, 4700 relays and 70 sensors, including radar, sonar, accelerometer, camera, rain sensors. Collectively, these devices generate more than 25 gigabytes of data per hour, which is processed by more than 70 on-board computers. 1 car year = 1TB 3
  4. 4. © 2014 IBM Corporation A Big Data & Analytics approach helps provide a foundation for a Smarter Enterprise Invest in aInvest in a big data & analyticsbig data & analytics platformplatform Be proactive aboutBe proactive about privacy, security andprivacy, security and governancegovernance Imagine It. Realise It. Trust It. Build a culture thatBuild a culture that infuses analyticsinfuses analytics everywhereeverywhere Confidence in Your Data Confidence in Accelerating Value Confidence in Your Skills 4
  5. 5. © 2014 IBM Corporation Deployed real-time CDR analysis solution to handle exploding data volume growth and performance requirements Analyzes call, internet usage, and text records in real-time to identify and address poorly performing cells Uses InfoSphere Streams and IBM Netezza Significant Benefits: Over 90% reduction in time to merge/load call record data Over 90% reduction in storage Increased network quality, improved customer satisfaction, reduced churn Sprint Increases Revenue & Improves Customer Satisfaction “Over 90+% reduction in merge/load times and storage requirements” “Over 90+% reduction in merge/load times and storage requirements” Capabilities Utilised: • Stream processing • Data Warehouse Analytics Appliance 5
  6. 6. © 2014 IBM Corporation • Examines trends, volume, and content of millions of public Twitter messages in real-time • Analytic accelerators to understand sentiment (positive, negative, neutral) • Capabilities • Stream Computing • Visualization • Benefits • Real-time display of public sentiment as candidates respond to questions • Debate winner prediction based on public opinion instead of solely political analysts University of Southern California Innovation Lab Monitors Political Debates Solution to measure public sentiment during key primary & general presidential debates 6
  7. 7. © 2014 IBM Corporation 7 KTH Swedish Royal Institute of Technology Reducing Traffic Congestion • Deployed real-time Smarter Traffic system to predict and improve traffic flow. • Analyzes streaming real-time data gathered from cameras at entry/exit to city, GPS data from taxis and trucks, and weather information. • Predicts best time and method to travel such as when to leave to catch a flight at the airport Significant benefits: • Enables ability to analyze and predict traffic faster and more accurately than ever before • Provides new insight into mechanisms that affect a complex traffic system • Smarter, more efficient, and more environmentally friendly traffic 7 Capabilities Utilised: Stream Computing 7
  8. 8. © 2014 IBM Corporation Pacific Northwest Smart Grid Demonstration Project Capabilities: Stream Computing – real-time control system Data Warehouse Appliance – analyze massive data sets Demonstrates scalability from 100 to 500K homes while retaining 10 years’ historical data 60k metered customers in 5 states Accommodates ad hoc analysis of price fluctuation, energy consumption profiles, risk, fraud detection, grid health, etc. 8
  9. 9. © 2014 IBM Corporation Information Integration & Governance Systems Security On premise, Cloud, As a service Storage IBM Watson Foundations IBM Big Data & Analytics Infrastructure New / Enhanced ApplicationsAll Data What action should I take? Decision management Cognitive What did I learn? 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, content and analysisWhat could happen? Predictive analytics and modelling Deep Analytics data zone 8 Realise It. Invest
  10. 10. © 2014 IBM Corporation Realise It. In-Store Presence Zones Intelligent location-based technology to gain deep insight into customer in-store behaviour Enable retailers to integrate the physical and digital experience to facilitate an ongoing dialogue that creates loyalty via an exceptional in-store shopping experience Presence Zones Sensors 9
  11. 11. © 2014 IBM Corporation IBM Internal Use Only Realise It. The Customer Insight Appliance 10
  12. 12. © 2014 IBM Corporation Realise It. A Multichannel Korean retailer Reliable insight provides decision support for senior management Targeted campaigns can be developed for marketing Precise measurement of cross-channel campaigns Business Challenge: As sales increased for this retailer’s online shopping mall, management experienced increasing difficulty ensuring that an appropriate product mix was being presented to its customers. The Solution: The company adopted sophisticated analytics and marketing automation to understand, predict and act on consumer buying behavior with confidence. Real-time marketing automation delivers personalised content to each shopper, triggered by their interaction history. Delivered at the right place and time, these offers can move the shopper toward a sale and even increase the size of the purchase. “We have greatly improved our understanding of our customers, which is helping us to make smarter decisions that significantly improve business performance.” —Spokesperson, multichannel Korean retailer Combining marketing automation with analytics to personalise communications and optimise offerings 11
  13. 13. © 2014 IBM Corporation Millions of events per second Microsecond Latency Traditional / Non-traditional data sources Real time delivery Powerful Analytics Algorithmic Trading Telco Churn Prediction Smart GridCyber Security Government / Law enforcement ICU Monitoring Environment MonitoringValue Clear business goals Business change driven outcomes Volume Terabytes/second Petabytes/day Variety All kinds of data All kinds of analytics Velocity Decisions in microseconds Massively scalable Veracity Screening, validation & certification of data Example Streaming Data Sources: Video, Audio, Networks, Social Media, Sensor, Weather Realise It. IBM InfoSphere Streams: Real-Time Adaptive Analytics for Big Data In-Motion Connected Car 11 3
  14. 14. © 2014 IBM Corporation Create foundation of trusted data Understand usage and monitor compliance Model exposure and understand variability Trust the factsTrust the facts Ensure privacyEnsure privacy and securityand security Make riskMake risk aware decisionsaware decisions Trust It. Be proactive about privacy, security and governance. 14
  15. 15. © 2014 IBM Corporation Big Data Uses Cases Delivered with Unique IBM Capabilities Unique IBM Capabilities: 1. In-memory computing with BLU Acceleration 2. Data privacy and security of big data 3. Data Discovery and Exploration 4. Building Confidence in Big Data with Information Governance 5. Stream computing WATSON FOUNDATIONS Decision Management Planning & Forecasting Discovery & Exploration Business Intelligence & Predictive Analytics Content Analytics Information Integration & Governance Data Mgmt & Warehouse Hadoop System Stream Computing Content Management WATSON FOUNDATIONS Decision Management Planning & Forecasting Discovery & Exploration Business Intelligence & Predictive AnalyticsBusiness Intelligence & Predictive Analytics Content Analytics Information Integration & Governance Data Mgmt & Warehouse Hadoop System Stream Computing Content Management Real-time traffic flow optimisation Low-latency network analysis Fraud & risk detection Predictive asset maintenance Understand and act on customer sentiment Predict and act on intent to purchase 15
  16. 16. © 2014 IBM Corporation 16
  17. 17. © 2014 IBM Corporation http://www.youtube.com/watch?v=FGp-h-x0Hss 17
  18. 18. © 2014 IBM Corporation Building a real-time enterprise is a journey, which depends on a solid Big Data & Analytics foundation for success Be proactive about privacy, security and governance Build a culture that infuses analytics everywhere Invest in a big data & analytics platform Imagine It. Realise It. Trust It. 18
  19. 19. © 2014 IBM Corporation Ian Radmore IBM Big Data Specialist, UK & Ireland IBM United Kingdom Limited City Gate West Toll House Hill Nottingham NG1 5FN Mobile +44 7843 368078 Ian.radmore@uk.ibm.com 19

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