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Open Source Adoption and Use in the Real World Summing up data warehousing & business intelligence: Transaction processing is a commodity. Analysis is not. 1 100 15 2 80 14 3 60 40 13 4 Smooth 20 0 Chunky 12 5 11 6 10


  1. Open Source Adoption and Use in the Real World

  2. Summing up data warehousing & business intelligence: Transaction processing is a commodity. Analysis is not. 1 100 15 2 80 14 3 60 40 13 4 Smooth 20 0 Chunky 12 5 11 6 10 7 9 8 Margin of error: +/- 100 points

  3. Cautionary Tale: Visions of Yesterday’s Future

  4. Cautionary Tale: Visions of Yesterday’s Future

  5. Cautionary Tale: Visions of Yesterday’s Future

  6. Cautionary Tale: Visions of Yesterday’s Future

  7. “Prediction is very difficult, especially about the future.” Niels Bohr

  8. Where the analysts are on the adoption curve “Open source is not worth paying attention to.” A Gartner analyst I don’t want to make too much fun of, January 2006

  9. “The future is the present projected.” Aldous Huxley

  10. What is the state of the enterprise software market today?

  11. Any Industry This Big is Maturing Annual US software sales 150 130 110 90 70 50 30 10 -10 70 75 80 85 90 95 00 Source: US Dept. of Commerce March 2009 Mark R. Madsen

  12. Evolution of the Software Market 1987 Source: John Prendergast (data: Bloomberg, Factset) March 2009 Mark R. Madsen

  13. Evolution of the Software Market 1997 Source: John Prendergast (data: Bloomberg, Factset) March 2009 Mark R. Madsen

  14. Evolution of the Software Market 2007 Source: John Prendergast (data: Bloomberg, Factset) March 2009 Mark R. Madsen

  15. The DW & BI Software Market Today According to IDC, the analytics and data warehouse software market is growing at 31,595 10.3% CAGR 28,682 26,001 23,601 21,408 19,342 17,386 2005 2006 2007 2008 2009 2010 2011 March 2009 Mark R. Madsen

  16. How to predict like an analyst.

  17. Moore’s Law via the Lens of the Industry Analyst CPU Speed Time

  18. Power Use Moore’s Law: Power Consumption 2019 Time

  19. CPU Temp Moore’s Law: Heat Generation 2019 Time

  20. Conclusion #1: Your own nuclear reactor by 2019 Power Use Time 2019

  21. Conclusion #2: You will need a new desk in 2019 CPU Temp Time 2019

  22. “If the automobile had followed Reality the same development as the computer, a Rolls-Royce would today cost $100, get a million miles per gallon, and explode once a year killing everyone Anything inside.” Robert Cringely Time

  23. The Real State of Enterprise Software? March 2009 Mark R. Madsen

  24. Software Revenue = Corporate IT Cost IT costs as a percent of equipment investment 50 40 30 20 10 0 68 72 76 80 84 88 92 96 00 04 Source: US Dept. of Commerce March 2009 Mark R. Madsen

  25. Enterprise Software Economics The enterprise software model is breaking down. Some facts: • 70% - 80% of sales & marketing is for new sales • 76% of new license revenue goes to sales & marketing • Maintenance makes up 45% of revenues and this number is increasing • 75% of R&D for mature products is for updates, bug fixing, and non- revenue enhancements • Maintenance and support is becoming the biggest factor is software company profitability. Sources Godman-Sachs, Tech Strategy Partners, Forrester March 2009 Mark R. Madsen

  26. BI is Entering Mainstream Adoption This means the BI market is entering a period of commodification: demand up, supply up, prices and margins down. Door open for OSS. Reporting Databases & Analysis Platforms Data Integration Predictive analytics March 2009 Mark R. Madsen

  27. Technology Priorities in IT Source: CIO Insight Informing the business trumps automating the business. This held true for three years in a row. March 2009 Mark R. Madsen

  28. Spending Priorities in IT In 2007 and 2008 IT budgeted most new project money for databases and business intelligence. Sources: CIO Insight March 2009 Mark R. Madsen

  29. Open Source Disruption “Which sector of the industry is most vulnerable to disruption by open source in the next five years?” 1. Web publishing and content management 2. Social software 3. Business Intelligence Source: North Bridge Venture Partners March 2009 Mark R. Madsen

  30. Signs of Maturity Source: Open Source Index 2008, Red Hat, Inc. March 2009 Mark R. Madsen

  31. Use of OSS BI/OLAP tools worldwide March 2009 Mark R. Madsen

  32. Open Source BI Use Looks Like Proprietary BI Use March 2009 Mark R. Madsen

  33. Rationale When Evaluating OSS March 2009 Mark R. Madsen

  34. Good News: It Works March 2009 Mark R. Madsen

  35. State of Adoption & Use of Open Source BI None Considering Completed Evaluation Using in Production 50% 45% 40% 33% 35% 30% 25% 21% 18% 20% 12% 15% 9% 10% 5% 0% Database / Reporting Data Embedded / Advanced DW platform and OLAP integration application analytics and ETL reports

  36. Data size for all survey respondents including those using proprietary databases. 50% 81% of the 45% 45% sample < 1TB 40% 35% 30% 22% 25% 20% 15% 9% 10% 7% 7% 7% 3% 5% 0% 0 ‐ 49 50 ‐ 100 100 ‐ 499 500 ‐ 999 1 ‐ 5 TB 5 ‐ 25 TB >25 TB

  37. Why did BI software evaluations fail? Missing or incomplete features 56% Scalability problems 41% Lack of available consulting 27% Difficulty integrating into environment 26% Required more expertise than expected 25% 0% 10% 20% 30% 40% 50% 60% March 2009 Mark R. Madsen

  38. There’s still work to be done

  39. Data is the future

  40. “When a new technology rolls over you, you're either part of Questions? the steamroller or part of the road.” – Stewart Brand March 2009 Mark R. Madsen

  41. We Could Use Your Help If you evaluated open source software for any aspect of the BI or data warehouse environment, please fill out the online open source adoption survey at http://bitly.com/scRhF The survey is running until May 30, 2009. March 2009 Mark R. Madsen

  42. Creative Commons Thanks to the people who made their images available via creative commons: highway storm.jpg - http://flickr.com/photos/areyoumyrik/235230688 firemen not noticing fire.jpg - http://flickr.com/photos/oldonliner/1485881035/ godzilla_vs_bhudda_big.jpg - http://flickr.com/photos/olivander/262293544/ acapluco_cliff_divers_cc.jpg - http://flickr.com/photos/raveller/ March 2009 Mark R. Madsen

  43. Creative Commons This work is licensed under the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/us/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA. March 2009 Mark R. Madsen

  44. MySQL Conference & Expo Bruce Belvin ‘

  45. Company Mission Monolith Software Solutions is dedicated to providing scalable business intelligence for multi-unit QSR restaurant operations.

  46. Open Source Components SUSE Linux Enterprise

  47. Overview � 3000+ disparate data sources � 4500 users � Complex organizational structures / hierarchy � Multi tenant environment � Segregated data bases per individual organization � Same data used for various business functions � Granular data

  48. Vertical Landscape I. Fragmented ownership II. Legacy hardware/various data sources III. Hesitancy to adopt Open Source IV. Small margin industry

  49. Why SaaS Works • Subscription business model fits segment price pressures • Unlimited users solves user heavy structure • Initial price / on going maintenance • Low barrier to entry • Pay as you go for additional integration/modules

  50. Keys to SaaS Success • Educate multiple decision making groups within organization • Utilize support from technology partners and open source community • Be aware of impact on IT/political past decisions • Prove open source solution • Develop silver bullet strategies to over come open source perceptions

  51. Background � President / COO of Consorte Media � Formerly CTO of BlueLithium, Adteractive, Fathom Online, and Cybernautics � 13 years as a technical executive in the online advertising industry 54

  52. Scope of Online Advertising Delivers the right ad to the right Dynamically person builds pages for visitor using predictive models Collect Metrics for performance measurement and analytics 55

  53. Business Challenges Web API Internal Applications Revised Models Analytics Data Mining Model Development Performance Reports 56

  54. Our Stack � CentOS � MySQL � BIRT � Hibernate � Apache � Camel � Kettle � Hadoop

  55. Best Practices Use analytics to design and test • advertising models using only relevant dimensions Gather and determine business • requirements before embarking on the journey Build an infrastructure plan that • will support the data collection and analytics platform 58

  56. The Role of Open Source Several important innovations in data • processing have been driven largely by online advertising Industry needs software and tools to • match pace of innovation and fast- changing business climate Proprietary software vendors unable to • respond quickly enough to support the industry Open Source has provided innovative • solutions and flexibility to support new business requirements 59

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