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The Emergence of Big Data

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Overview of the emerging Big Data market and the growth of the Hadoop Ecosystem - forecast for growth, important segments and start-up funding

Overview of the emerging Big Data market and the growth of the Hadoop Ecosystem - forecast for growth, important segments and start-up funding

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  • 1. Big DataInternet Research GroupApril, 2012John Katsaros jkatsaros@irg-intl.com 1
  • 2. In 2011 organizations realized that they were sitting on aninformation goldmine. Rather than discarding datasetswhich seemed too costly to analyze, they have reached thepoint where a business can affordably analyze vast amountsof information and unlock valuable insights. 2
  • 3. A new industry was launched – Big Data 3
  • 4. Big Data can trace its roots to Google when in 2004 twoGoogle engineers, Jeffery Dean and SanjayGhemawat, published a Usenix paper describingMapReduce – Simplified Data Processing on Large Clusters.Subsequently Doug Cutting at Yahoo! developed an opensource version named Hadoop. 4
  • 5. Big Data Market (M)$1,600$1,400$1,200$1,000 $800 $600 $400 $200 $- 2011 2012 2013 2014 2015 2016 Source: IRG ResearchThe Big Data Market hit the radar in 2011 5
  • 6. Big Data is often machine generated and includes, but is not limited to, click stream data, log files, (servers, network equipment, apps…) alerts (network, security devices …) and social media content. AlertsClick Stream 6 6 Logs Social Media
  • 7. At the same time MapReduce was developing, server prices continued to drop and Amazon’s AWS service began offering servers priced on a time basis – these events made computing more affordable, especially for Big Data applications. Server PricesServer = 8 cents/hour 7
  • 8. The early adopters of Big Data ran large Web properties like e-Bay and Facebook – organizations that had a lot of click stream data and large numbers of registered users.1. Personalize the visit – lead to longer visits2. Spam mitigation – reduce annoyance3. Suggesting friends you may know – increases member interconnections 8
  • 9. Recently enterprises which operate large Web sites have begun working with Hadoop and Big Data1. Customize the visit – increase brand awareness2. Suggesting products (e.g., financial services)3. Cross selling/multi-channel (e.g., Disney) CRM 9
  • 10. Enterprise adoption of Big Data will grow quickly and in 18months spending will exceed the amount spent by largeWebsites. Big Data Segment Spending Comparison Enterprises Large Web Sites 2011 2012 2013 2014 2015 2016 10 Source: IRG Research Source: IRG Research
  • 11. In 2013 Enterprise Big Data Spending will surpass LargeWebsite Spending Big Data Segment Spending Forecast (M) $1,200 $1,000 $800 $600 Enterprises $400 Large Web Sites $200 $- 2011 2012 2013 2014 2015 2016 Source: IRG Research 11
  • 12. Finally, when (and how) will SMB’s and Enterprises not running large web properties adopt Big Data Technology?1. When Business Intelligence products become useable and widely available2. Through platforms like Splunk which already has 3,500 IT user organizations3. When SMBs are presented with compelling value propositions 12
  • 13. Meanwhile Big Data developers are extending functionalityranging from better easier to manage systems to higherperformance systems to simplified Business Intelligenceplatforms. Source: Hortonworks 13
  • 14. There seems to be plenty of money available to fund BigData companies Accel Partners Launches $100mm Big Data Fund Accels Big Data Fund aims to fund transformative early stage and growth companies throughout the Big Data ecosystem, from next generation storage and data management platforms to a wide range of revolutionary software applications and services – i.e. data analytics, business intelligence, collaboration, mobile, vertical applications and many more. We believe the future multi-billion software companies will be emerge from the Big Data ecosystem. 14
  • 15. No SQL The Hadoop EcologyHadoop Releases Big Data Analytics Hadoop Infrastructure Management HStreaming Data Presentation Data Integration
  • 16. Our list of interesting Big Data startups Company Investment Investors Location Sequoia, Flybridge and Union 10gen $31M Redwood Shores, CA Square Ventures YCombinator, True Ventures, BackType $1.32M San Francisco, CA lowercase, Freestyle Greylock, Meritech Capital, Cloudera $76M Palo Alto, CA Accel, Ignition Partners Accel Partners, Ignition Couchbase $30M Partners, Mayfield, North Mountain View, CA Bridge, Docomo DataStax $13.7M Lightspeed, Crosslink Capital Burlingame, CA Datameer $11.75M Kleiner Perkins, Redpoint San Mateo, CA Norwest Venture Partners, Hadapt $9.5M Cambridge, MA Bessemer Venture Partners HortonWorks Benchmark Capital Sunnyvale, CA HStreaming Chicago, IL Karmasphere $5M Hummer, Winblad, USVP Cupertino, CA Kitenga Santa Clara, CA MapR Technologies $9M Lightspeed, NEA San Jose, CA Mintigo $9M Sequoia, Giza Menlo Park, CA Neo Technologies $10.6M Fidelity, Sunstone, Conor Menlo Park, CA Pentaho $32M Benchmark, Index, NEA Orlando, FL StackIQ $3M Antham, Avalon La Jolla, CA Balderton Capital, AGF Talend $28M Private Equity, Galileo Los Altos, CA Partners NEA, Meritech Capital Tableau Software $15M Seattle, WA Partners Total Investment $284+ 16
  • 17. And the Venture Companies that Funded these startups C S F UYT L F GMA I N DML CKR NB BHUNAABAG I F S CG o e l n - r o r r c g o o i r l e o e e u S En v aGa n i u o i m q y i Cu w e e e c n r c a g o i d r s n mV A t a l F l d d n n z p u - o o e e e- y r e i t o y h s n p w s c mP h l d i e e s o a a o b nm r S l i l t hmf t s e o e e h e a o e l x l t r n i r Sb - t o t i b o i s L r i s mm r mn r e i o y a i q C y c e o r e p i n t e a w t o d n d u a l k c n i l e n t r r i o y e g a s e h d d e k k n n r e g d b e e l a d 10gen XXX BackType XXXX Cloudera XXXX Couchbase XXXXX DataStax XX Datameer XX Hadapt XX HortonWorks X HStreaming Karmasphere XX Kitenga MapR X X Technologies Mintigo X X Neo XXX Technologies Pentaho X X X StackIQ XX Talend XXX Tableau X X Software 17
  • 18. Thank YouJohn Katsaros jkatsaros@irg-intl.com 18

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