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Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
Hortonworks for Financial Analysts Presentation
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Hortonworks for Financial Analysts Presentation

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Hortonworks presentation from Cowen Big Data Day for financial industry analysts

Hortonworks presentation from Cowen Big Data Day for financial industry analysts

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  • Our commitment to Apache has already changed the market!Ultimately contributing the code that maters and making it work is the currency in open source
  • Our commitment is to continue growing our contribution
  • For more information on the history of Hadoop, see: http://developer.yahoo.com/blogs/hadoop/posts/2011/01/the-backstory-of-yahoo-and-hadoop/
  • Transcript

    • 1. Hortonworks<br />Eric Baldeschwieler, Co-Founder and CEO<br />September 2011<br />Overview for Cowen Big Data Day 2011<br />© Hortonworks Inc. 2011<br />
    • 2. Agenda<br />Hortonworks<br />Apache Hadoop<br />Use cases<br />Hadoop in the Enterprise<br />Market<br />Strategy<br />2<br />© Hortonworks Inc. 2011<br />
    • 3. About Hortonworks – Basics<br />Founded – July 1st, 2011<br /> 22 architects & committers from Yahoo!<br />Mission – Architect the future of Big Data<br /> Revolutionize and commoditize the storage and processing of Big Data via open source<br />Vision – Half of the worlds data will be stored in Hadoop within five years<br />3<br />© Hortonworks Inc. 2011<br />
    • 4. About Hortonworks – Game Plan<br />Support the growth of a huge Apache Hadoop ecosystem<br />Invest in ease of use, management, and other enterprise features<br />Define APIs for ISVs, OEMs and others to integrate with Apache Hadoop<br />Continue to invest in advancing the Hadoop core, remain the experts<br />Contribute all of our work to Apache<br />Profit by providing training & support to the Hadoop community<br />4<br />© Hortonworks Inc. 2011<br />
    • 5. Credentials<br />Technical: key architects and committers from Yahoo! Hadoop engineering team<br />Delivered every major Apache Hadoop release since 0.1<br />Highest concentration of Apache Hadoop committers<br />Driving innovation across entire Apache Hadoop stack<br />Experience managing world’s largest deployment<br />Access to Yahoo!’s 1,000+ users and 42k+ nodes for testing, QA, etc.<br />Business operations: team of highly successful open source veterans<br />Led by Rob Bearden, former COO of SpringSource & JBoss<br />Investors: backed by Benchmark Capital and Yahoo!<br />5<br />© Hortonworks Inc. 2011<br />
    • 6. What is Apache Hadoop?<br />Set of open source projects <br />Owned by Apache Software Foundation<br />Transforms commodity hardware into a service that:<br />Stores petabytes of data reliably (HDFS)<br />Allows huge distributed computations (MapReduce)<br />Key attributes:<br />Redundant and reliable<br />Doesn’t stop or lose data even if hardware fails<br />Easy to program<br />Extremely powerful<br />Allows the development of big data algorithms & tools<br />Batch processing centric <br />Runs on commodity hardware<br />Computers & network<br />6<br />© Hortonworks Inc. 2011<br />
    • 7. Typical Hadoop Applications<br />7<br />data analytics<br />advertising optimization<br />machine learning search ranking<br />Mail anti-spam<br />advertising data systems<br />audience, ad and search pipelines<br />ad selection<br />Website personalization<br />Content Optimization<br />ad inventory prediction<br />user interest prediction<br />© Hortonworks Inc. 2011<br />
    • 8. Who Builds Hadoop?Lines of code contributed since Hadoop inception<br />8<br />© Hortonworks Inc. 2011<br />
    • 9. Who Builds Hadoop?Lines of code contributed in 2011<br />9<br />© Hortonworks Inc. 2011<br />
    • 10. , early adopters <br />Scale and productize Hadoop<br />2006 – present<br />Other Internet Companies<br />Add tools / frameworks, enhance Hadoop<br />2008 – present<br />Service Providers <br />Provide training, support, hosting <br />2010 – present<br />Apache Hadoop<br />A Brief History<br />Nascent / 2011<br />Wide Enterprise Adoption <br />Funds further development, enhancements<br />10<br />© Hortonworks Inc. 2011<br />
    • 11. HADOOP @ YAHOO!<br />40K+ Servers<br />170 PB Storage<br />5M+ Monthly Jobs<br />1000+ Active users<br />© Yahoo 2011<br />11<br />
    • 12. CASE STUDY<br />YAHOO! HOMEPAGE<br /> twice the engagement<br />Personalized<br />for each visitor<br />Result: <br />twice the engagement<br />News Interests<br />Top Searches<br />Recommended links<br />+43% clicks<br />vs. editor selected<br />+79% clicks<br />vs. randomly selected<br />+160% clicks<br />vs. one size fits all<br />© Yahoo 2011<br />12<br />
    • 13. CASE STUDY<br />YAHOO! HOMEPAGE<br /> SCIENCE<br /> HADOOP <br /> CLUSTER<br /><ul><li>ServingMaps
    • 14. Users - Interests
    • 15. Five Minute Production
    • 16. Weekly Categorization models</li></ul>»Machine learning to build ever better categorization models<br />CATEGORIZATION<br />MODELS (weekly)<br />USER<br />BEHAVIOR<br /> PRODUCTION<br /> HADOOP <br /> CLUSTER<br />»Identify user interests using Categorization models<br />SERVING<br />MAPS<br />(every 5 minutes)<br />USER<br />BEHAVIOR<br />Build customized home pages with latest data (thousands / second)<br />SERVING SYSTEMS<br />ENGAGED USERS<br />© Yahoo 2011<br />13<br />13<br />
    • 17. CASE STUDY<br />YAHOO! MAIL<br />Enabling quick response in the spam arms race<br />SCIENCE<br /><ul><li>450M mail boxes
    • 18. 5B+ deliveries/day
    • 19. Antispam models retrained</li></ul> every few hours on Hadoop<br />PRODUCTION<br />“<br />40% less spam than Hotmail and 55% less spam than Gmail<br />“<br />© Yahoo 2011<br />14<br />14<br />
    • 20. Hadoop in the Enterprise<br />© Hortonworks Inc. 2011<br />15<br />
    • 21. Big Data PlatformsCost per TB, Adoption<br />Size of bubble = cost effectiveness of solution<br />Source: <br />16<br />© Hortonworks Inc. 2011<br />
    • 22. Traditional Enterprise ArchitectureData Silos + ETL<br />17<br />Traditional Data Warehouses, <br />BI & Analytics<br />Serving Applications<br />Web Serving<br />NoSQLRDMS<br />…<br />Traditional ETL &<br />Message buses<br />EDW<br />Data Marts<br />BI / Analytics<br />Traditional ETL &<br />Message buses<br />Serving Logs<br />Social Media<br />Sensor Data<br />Text Systems<br />…<br />Unstructured Systems<br />© Hortonworks Inc. 2011<br />
    • 23. Hadoop Enterprise ArchitectureConnecting All of Your Big Data <br />18<br />Traditional Data Warehouses, <br />BI & Analytics<br />Serving Applications<br />Web Serving<br />NoSQLRDMS<br />…<br />Traditional ETL &<br />Message buses<br />EDW<br />Data Marts<br />BI / Analytics<br />Apache Hadoop<br />EsTsL (s = Store) <br />Custom Analytics<br />Traditional ETL &<br />Message buses<br />Serving Logs<br />Social Media<br />Sensor Data<br />Text Systems<br />…<br />Unstructured Systems<br />© Hortonworks Inc. 2011<br />
    • 24. Hadoop Enterprise ArchitectureConnecting All of Your Big Data <br />19<br />Traditional Data Warehouses, <br />BI & Analytics<br />Serving Applications<br />Web Serving<br />NoSQLRDMS<br />…<br />Traditional ETL &<br />Message buses<br />EDW<br />Data Marts<br />BI / Analytics<br />Apache Hadoop<br />EsTsL (s = Store) <br />Custom Analytics<br />Gartner predicts <br />800% data growth <br />over next 5 years<br />80-90% of data <br />produced today <br />is unstructured<br />Traditional ETL &<br />Message buses<br />Serving Logs<br />Social Media<br />Sensor Data<br />Text Systems<br />…<br />Unstructured Systems<br />© Hortonworks Inc. 2011<br />
    • 25. The Hadoop Market<br />© Hortonworks Inc. 2011<br />20<br />
    • 26. Market Drivers for Apache Hadoop<br />Business drivers<br />Identified high value projects that require use of more data<br />Belief that there is great ROI in mastering big data<br />Financial drivers<br />Growing cost of data systems as proportion of IT spend<br />Cost advantage of commodity hardware + open source <br />Enables departmental-level big data strategies <br />Technical drivers<br />Existing solutions failing under growing requirements<br />3Vs - Volume, velocity, variety<br />Proliferation of unstructured data<br />21<br />Significant opportunity for Hadoop in enterprise data architectures<br />© Hortonworks Inc. 2011<br />
    • 27. Market Opportunity for Hadoop<br />Current<br />Apache Hadoop can become de facto platform for managing unstructured data in the enterprise<br />Enable new breed of applications to be built on top of Apache Hadoop<br />Future<br />Hadoop becomes the next generation enterprise data architecture<br />22<br />© Hortonworks Inc. 2011<br />
    • 28. Market Dynamics<br />Technology & knowledge gaps are preventing Apache Hadoop from becoming an enterprise standard<br />Difficult to install and deploy Hadoop projects <br />Lack of technical content to assist<br />Demand for knowledgeable developers far exceeds supply<br />Virtually every F500 company is constructing a Hadoop strategy<br />But most are still in POC/experimentation phase with Hadoop<br />Top ISV/OEMs working to create Hadoop strategies<br />Driven by customer demand<br />Community is becoming increasingly confused by all of the noise<br />Multiple distributions, many vendor announcements<br />Fear of market fragmentation<br />23<br />© Hortonworks Inc. 2011<br />
    • 29. Conclusion<br />There is not a Hadoop market to “win” today<br />Most organizations haven’t moved to full-scale production<br />Lack of mass adoption limiting short-term monetization opportunities<br />Need to drive Apache Hadoop as a unifying standard<br />In order to succeed, we need to enable the market<br />Continue investment to overcome technology gaps<br />Enable a vibrant partner ecosystem<br />Expand availability of content and services to address knowledge gaps<br /> How will Hortonworks do that?<br />24<br />© Hortonworks Inc. 2011<br />
    • 30. Hortonworks Strategy<br />© Hortonworks Inc. 2011<br />25<br />
    • 31. Hortonworks Strategy #1Overcome Technology Gaps<br />Make Apache Hadoop projects easier to install, manage & use<br />Regular sustaining releases<br />Projects released as binary (RPM, .deb)<br />Open source Management & Monitoring<br />Make Apache Hadoop more robust<br />Performance gains<br />High availability<br />Administration & monitoring <br />All done within Apache Hadoop community<br /><ul><li>Develop collaboratively with community
    • 32. Complete transparency
    • 33. All code contributed back to Apache</li></ul>Anyone should be able to easily deploy the Hadoop projects from Apache<br />26<br />© Hortonworks Inc. 2011<br />
    • 34. HortonworksStrategy #2Enable a Vibrant Ecosystem<br />Unify the community around a strong Apache Hadoop offering<br />Make Apache Hadoop easier to integrate & extend<br />Work closely with partners to define and build open APIs<br />Everything contributed back to Apache<br />Provide enablement services as necessary to optimize integration<br />27<br />Integration & Services Partners<br />Hadoop Application Partners<br />DW, Analytics & BI Partners<br />Serving & Unstructured Data Systems Partners<br />Hardware Partners<br />Cloud & Hosting Platform Partners<br />© Hortonworks Inc. 2011<br />
    • 35. Hortonworks Strategy #3Overcome Knowledge Gaps<br />Improve user experience with Apache Hadoop software<br />Binaries, installers, etc.<br />Expand Apache Hadoop technical content<br />Core content on Apache.org<br />Docs, installation guides, etc.<br />Advanced tools on Hortonworks.com<br />Best practices, screencasts, forums, etc.<br />Extensive Hadoop training & certification program<br />Expert technical support services<br />28<br />© Hortonworks Inc. 2011<br />
    • 36. Rationale for Hortonworks Strategy<br />Strong interest from community (enterprises and ISV/OEMs) in a complete, enterprise-viable, Apache Hadoop platform<br />Strong desire for core to remain unified and strong, avoid UNIX wars II<br />Fremium model seen as a barrier to growth and adoption<br />Highly defensible because of Hortonworks leadership in core projects<br />Proven experience executing open source business models<br />Rob Bearden & Benchmark<br />29<br />© Hortonworks Inc. 2011<br />
    • 37. 30<br />Thank You.<br />© Hortonworks Inc. 2011<br />

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