The Formula for Hadoop Project Success


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As the big data market matures, Hadoop discussions are expanding from pure technology to how businesses can use it to drive innovation and leap-frog competition. In this session, Karmasphere will outline how to successfully deploy Hadoop projects by bringing together the right people, technology and use cases. We will discuss the optimal project team, the role of data scientists and analysts, the new big data analytics workflow and use cases for driving rapid ROI and success.

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  • Transform PMML models to standard Hadoop UDF’s. Leverage the power of Hadoop to score models across all data in Hadoop and increase their accuracy.
  • Today we are previewing Karmasphere 3.0 capabilities. One of the key new features we announced is the availability of a personalized Analytics dashboard. The dashboard helps users organize their big data analytics, presents the users with relevant analytics work products at their fingertips. It also provides activity status so you can complete projects on time and on budget
  • The Formula for Hadoop Project Success

    1. 1. Volume, Variety and Velocity all increasing rapidly Source: IBM, Oct 2012 OMG!…The Opportunity Is Huge
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    3. 3. InformationWeek 2013 There’s certainly challenges
    4. 4. A Success Formula for a Hadoop Project ✚= = WHAT your company & you HOW best practices
    5. 5. MORE BI?
    6. 6. What Can We Make Happen? “Data Platform of Intent” Big Data Full Fidelity Analysis Unstructured Behavioral, Open, Affordable HADOOP HQL BI Data Cube Analysis Structured, Transact ional Closed, Expensive RDBS & EDW SQL Powered by the CommunityPowered by Vendors Report On What Happened? Database of Transactions
    7. 7. 1. What auxiliary products should we recommend? 1. What new features should our product have? 1. How can we eliminate support issues? Hadoop Innovation Use Cases … some examples
    8. 8. Another Idea Score Your Predictive Models On Hadoop Model Builder Model Description Hive UDFs Standard Hive
    9. 9. Reinvent Your Career Lead Thrive
    10. 10. This is the time to be the river, not the rock
    11. 11. Big Data Projects on Hadoop We’re On a journey that’s just starting You Are Here….Time to get going!
    12. 12. But first!  Education  Training  Certifications
    13. 13. #1. Form a Partnership With LOB  Find a use case  Identify some budget  Form a project team  Be willing to educate others  Partner on a small POC, don’t boil the ocean Hadoop Project Success Best Practice #1
    14. 14. Teams are Highly Cross-Functional  Product Manager (LOB)  Power Analysts (IT or LOB)  Business Analyst (LOB)  Product Manager (LOB  IT Architect (IT)  Project Manager (IT/LOB)
    15. 15. “By 2016 the CMO will have more budget than the CIO” - Gartner Group Marketing The “Budget Richest” LOB?
    16. 16. #2. Use the Right Big Data Analytics tooling • Supports the entire time • Reuse and share for speed and efficiency • Leverage pre-built analytics Hadoop Project Success Best Practice #2
    18. 18. #3. Embrace Full Fidelity Big Data Analytics  Not sampled, all the data – maintains richness  Don’t replicate or move the data  Keep complexity and TCO low Hadoop Project Success Best Practice #3
    19. 19. Data Warehouse OLTP to OLAP Mapping Analyst In Summary In BI, The Analyst Was at the End of the Process Ordering App Financial App Master Data Staging OLAP Reports BI Using Data Cube Analysis Structured, Sampled Transitional, Closed , Expensive RDBS & EDW SQL Driven by Vendors
    20. 20. In Big Data Analytics on Hadoop The Analyst is at the Center of the Process Application AnalyticsData Unstructured Behavioral, Open, Affordable HADOOP HQL Analyst Full Fidelitiy Analytics
    21. 21. Get distracted….
    22. 22. Or Big Data on Hadoop Project
    23. 23. Thank You We’re happy to help Questions