Dedicated to solving strategic 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@example.com “It is a very sad thing that nowadays there is so little useless information,” Oscar Wilde, 1894.www.themetisfiles.com 2012
CIO Travel Guide Got AnExtra Destination In 2012Agenda:1. Where did Big Data come from?2. The promise of Big Data3. Where does it fit4. Now, later or never?5. Big Data trends to watch6. Things about data you should realize7. Recommendations + Conclusions Source: The METISfiles 2012
Data Explosion Was Waiting To HappenComputers have been around forover 60 years generating andprocessing data.• Growing Numbers of Digital Enabled Devices• Growing Number of App(lication)s• Growing Content Creation• Access Anywhere, Anytime, AnyhowConsumerization of IT is the flyweelof the data explosion
Data Explosion Still Waiting 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
What makes Data Big?• Volume: relative size of data sources• Velocity: speed at which data refresh is Variability Veracity handled Variety Vicosity• Variety: handling various data formatsBut 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 peopleAnd there is• Value: is why we are doing this Big Data is NOT a Panacea Source: The METISfiles 2012
THE PROMISE: Delivering The 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!
WHERE DOES BIG DATA 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 DiscoveryValue Chain Prioritizes Big Data Objectives Data Discovery Source: The METISfiles 2012
Big Dilemma: Now, Later or Never?Now is the time to rethink your Big Data can be implemented Never is not an optioninformation needs and how to later: it will no go away. Now isachieve those the time to think about it
Trends to Watch in 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
ABOUT BIG DATABusiness: 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
Big Data – Big DecisionsA study on Big Data and Big Analyticsin The Netherlands, 2013•User Perspectives on BD •Business •IT•User Deployment Plans•Build or Buy or Rent•Big Data Objectives•Preferred Suppliers•Big Data BudgetsFor more information mail meat firstname.lastname@example.org Thank You
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