Big Data, Big Decisions

Big Data, Big Decisions

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  Dedicated to solvingstrategic issues for executives in the Internet, IT and telecommunications industry Big Data, Big Decisions Marcel Warmerdam Principal Analyst at The METISfiles Dutch Datacenter & Hosting Summit 2012 [email protected] “It is a very sad thing that nowadays there is so little useless information,” Oscar Wilde, 1894. www.themetisfiles.com 2012
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  CIO Travel GuideGot An Extra Destination In 2012 Agenda: 1. Where did Big Data come from? 2. The promise of Big Data 3. Where does it fit 4. Now, later or never? 5. Big Data trends to watch 6. Things about data you should realize 7. Recommendations + Conclusions Source: The METISfiles 2012
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  Data Explosion WasWaiting To Happen Computers have been around for over 60 years generating and processing data. • Growing Numbers of Digital Enabled Devices • Growing Number of App(lication)s • Growing Content Creation • Access Anywhere, Anytime, Anyhow Consumerization of IT is the flyweel of the data explosion
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  Data Explosion StillWaiting To Happen Exabytes 1,200.00 ZB 1,000.00 800.00 • Explosion of photo’s and realtime 600.00 footage 400.00 • YouTube adding 24h of footage every 200.00 2 minutes: EB 0.00 PB 2021 2000 2003 2006 2009 2012 2015 2018 2024 2027 2030 • A project in the Large Hadron Collider will generate one petabyte per second. Exabytes • Things on the Internet will add another magnitude to the data ZB 1,000.00 explosion 100.00 • Sensor data will flood the Internet 10.00 • Any data we can capture will be EB 1.00 2012 2000 2003 2006 2009 2015 2018 2021 2024 2027 2030 captured 0.10 0.01 0.00 PB Annual content creation grows at 40 to 50% p.y. . Doubles every 2 year
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  What makes DataBig? • Volume: relative size of data sources • Velocity: speed at which data refresh is Variability Veracity handled Variety Vicosity • Variety: handling various data formats But there is more: Velocity Virality • Variability: number of data sources to be handled or variance within a dataset • Veracity: doubtfullness of data Big Data Volume Value • Viscosity: resistance to flow in the Complexity volume of data • Virality: speeds at which data disperses from people to people And there is • Value: is why we are doing this Big Data is NOT a Panacea Source: The METISfiles 2012
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  THE PROMISE: DeliveringThe Value of Big Data • Enhance customer satisfaction • Improve target marketing • Increase conversion rates • Improve customer loyalty • Improve brand value • Understand customer behavior • Facilitate innovation • Increase competiveness • Improve efficiency • Grow profits!
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  WHERE DOES BIGDATA FIT? Fitting Big Data into your company Real Time Data • Cost Control • Revenue Building Real Time Real Time • New Business Models/Innovation Adaptive Adaptive Processes Enterprise Operations Business Process Business Optimization Discovery Value Chain Prioritizes Big Data Objectives Data Discovery Source: The METISfiles 2012
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  Big Dilemma: Now,Later or Never? Now is the time to rethink your Big Data can be implemented Never is not an option information needs and how to later: it will no go away. Now is achieve those the time to think about it
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  Trends to Watchin Big Data •The Big Data Vendor consolidation game in 2011 •The acquisition of Greenplum by EMC •IBM’s Hadoop ++ based Infosphere BigInsights announcement completes the prior acquisitions of Cognos, SPSS and Infosphere Warehouse •Teradata’s acquisition of Aster Data •SAP announced HANA (High Performance Analytical Appliance) roadmap •Hewlett-Packard acquisition of Autonomy, Vertica Systems, Mulesoft and Soasta •Dell and Cloudera announced a n Hadoop Apache solution •Oracle released its Big Data Appliance and exalogic • Maturing of Cloud Offerings in Big Data: watch for Big Data as a Service • Watch for Data Brokers and Data Collectors joining the Big Data Ecosystem
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  IS MORE DATA THEANSWER TO EVERYTHING?
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  ABOUT BIG DATA Business: IT:  Data driven is NOT Fact  Build, buy or rent? Driven  Lots of challenges, lots  TOC and ROI: Is there a of opportunity business case?  Be the tour guide, not  Beware of the FUD the operator! factor  Think Big, Start Small  Think Big, Start Small
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  Big Data –Big Decisions A study on Big Data and Big Analytics in The Netherlands, 2013 •User Perspectives on BD •Business •IT •User Deployment Plans •Build or Buy or Rent •Big Data Objectives •Preferred Suppliers •Big Data Budgets For more information mail me at [email protected] Thank You