Nava levy big data for cc adapt or die - march 29th 2012 final


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Nava levy big data for cc adapt or die - march 29th 2012 final

  1. 1. When Cloud Meets Big Datas The drivers and use cases of big data analytics in the cloud Nava Levy, VP SaaS/Cloud Services March 29, 2012© 2012 – PROPRIETARY AND CONFIDENTIAL INFORMATION OF CVIDYA
  2. 2. Big Data as a Must Have Competency “Big Data will earn its place as the next "must have" competency in 2012 as the volume of digital content grows to 2.7 zettabytes (ZB), up 48% from 2011. Over 90% of this information will be unstructured – full of rich information, but challenging to understand and analyze” Source: IDC, December, 2011 2
  3. 3. Outline  cVidya overview  What is Big Data and what’s the hype is all about?  The Drivers for Big Data  Opportunities and use cases  Summary3
  4. 4. cVidya OverviewA global leader and innovative provider of Analytics and BI solutions forRevenue Intelligence for Telecom, Media and Entertainment service providers  Over 150 customers  Partnership with the world leading vendors – 7 out of the 10 largest operators  #1 Revenue Management Global Market Provider by (April 2011)  Analyzing over 1.5 Billion subscribers and  TM Forum Leadership billions of events daily  cVidyaCloud : Revenue Intelligence On  300 employees Demand for Service Providers of all sizes  Global presence in 20 locations4
  5. 5. Big Data in the Headlines IBM Cloud Harnesses Hadoop Elephant Apache Wired, October 2011 Oracle Taps Cloudera Hadoop awarded for Hadoop"Innovator of the Year“, Distribution of Big described as the Data Appliance Big Data will earn its place as the The VC behind TechCrunch,"Swiss Army Knife of next "must have" competency in January, 2012 the 21st century Facebook, Groupon, is 2012 ….Over 90% of this creating $100M fund The guardian, May, 2011 information will be unstructured – dedicated to Big Data. Forbes, Hadoop-based startup full of rich information, but November, 2011 challenging to understand and Cloudera raises $40M analyze” from Ignition Partners, HP yokes Autonomy, “Cloud and Big Data Accel, Greylock Vertica together for IDC: December, 2011 are the most Deals & More: big data push sweeping trends in IT” November 2011 Gigaom, November, EMC CEO, March, 2011 2011 Gartner predicts tha t data will grow by 800 percent in five Microsoft Embraces Big data: The next frontier Aster Data helps years, and 80% of Elephant of Open Source for innovation, Teradata embrace which is competition, Hadoop, ditching its Big Data unstructured| and productivity Gartner, 2011 proprietary platform Mckinsey Global Institute: Ovum, October 2011 June, 2011
  6. 6. What is Big Data? “Big Data is becoming a metaphor for: - Increasing volume of information - Finding information in previously ignored or new data types - Hadoop, MapReduce” Gartner, June 2011 “Storing, managing and analyzing massive and ever growing sets of data, mostly unstructured or semi structured, over clusters of commodity hardware, using NoSQL /non RDBMS technologies as Hadoop and Cassandra. The challenges and opportunities that it presents.”
  7. 7. Why? Tsunami - 4 Waves at Once! Big Data Mobile Social Cloud 7
  8. 8. Explosive Growth of Data - Mostly Unstructured Data will grow by 800 percent in five years, 80% of which is Stuctured unstructured 20% Gartner, 2011 Unstructured 80% 8
  9. 9. Explosive Growth of Unstructured Data Interaction data = unstructured or semi structure data Transaction data =structured data = relational data Source: IDC 9
  10. 10. The Big Data Paradox  Technology: Traditional RDBMS were not designed to address big data – RDBMS comply with ACID properties that were developed in the 70s… are not as relevant to big data – In addition, low value density of Big Data needs a new approach  People: According to Mckinsey report, US alone faces shortage of over 1.5M people in the analysts & science domains Data volumes growing faster than people11 skills, disk, plant and power
  11. 11. What is Hadoop? “Swiss Army Knife of the 21st century” Hadoop is a collection of open-source, distributed data-processing components for storing and managing large volumes of structured, unstructured, or semi structured data. It enables applications to work with thousands of nodes and petabytes of data. Hadoop runs on low-cost commodity hardware, and it scales up into the petabyte range at a fraction of the cost of commercial storage and data-processing alternatives. 12 Source: Informatica
  12. 12. Big Data & Cloud  Big Data is a private use case for Cloud Big Data / Analytics SaaS Applications  It was produced by cloud providers Software/ Application  The early adopters of Big Data are cloud Open Source Platforms as PaaS Hadoop MapReduce, providers Platform/ Middleware Cassandra  Available by most IaaS & PaaS providers IaaS Low cost commodity  The vast majority of its implementations hardware Infrastructure/Hardware are in the cloud Big Data is Cloud13
  13. 13. Opportunities & Use Cases Start-ups Established B2C & B2B Software Vendors Enterprises14
  14. 14. Startups  Big Data wave is disrupting traditional IT  Opportunities exist cross every layer of the “Big Data Stack”  In the application layer we can divide companies into 2 categories – When Business Model = Value Proposition = Big Data (BI “$100M dedicated to fund & analytics apps, Data visualization) entrepreneurs globally in building disruptive, Big Data companies” – When only the business model equals to Big Data but what drives customers to buy is different15
  15. 15. Established Software Vendors  Big Data platforms such as Hadoop are becoming mainstream as established infra vendors are embracing Big Data  Now is the time also for software vendors to adapt their applications to Big Data  Adapt in terms of taking advantage of NoSQL platforms and cloud infra, integrating with new data sources and adding features taking advantage of big data Source: Accel The biggest opportunity will rise from linking new data with transactional data16
  16. 16. B2C & B2B Enterprises & Specific Verticals – Acting on New Business/Internal and Public DataSource: Gartner, 2011 17
  17. 17. B2C & B2B Enterprises & Specific Verticals – Acting on New Business and Public Data Example for Use Cases  Sentiment analysis  Recommendation engines A Pattern-Based Strategy provides a framework to proactively seek patterns  Consumer behavior from traditional and non-traditional information sources, model their impact,  Personal sensors monitoring and adapt according to the requirements of the pattern.  Website behavior18
  18. 18. Summary  Data is exploding, with new data types that are breaking legacy data platforms  Big Data platforms such as Hadoop are becoming mainstream  Opens opportunities for startups, established ISVs and B2B / B2C enterprises to capitalize  The time to act is now!19
  19. 19. THANK YOU!