The Formula for Hadoop Project Success

1. The Formula for Hadoop Project Success Gail Ennis CEO

2. OMG!…The Opportunity Is Huge Volume, Variety and Velocity all increasing rapidly Source: IBM, Oct 2012

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4. There’s certainly challenges InformationWeek 2013

5. A Success Formula for a Hadoop Project = ✚ = WHAT your company & you HOWbest practices

6. MORE BI?

7. Big Data Analytics

8. Report On What Happened? Database of Transactions What Can We Make Happen? “Data Platform of Intent” BI Data Cube Analysis Big Data Full Fidelity Analysis • SQL • HQL • RDBS & EDW • HADOOP • Structured, Transactional • Closed, Expensive • Unstructured Behavioral, • Open, Affordable Powered by Vendors Powered by the Community

9. Hadoop Innovation Use Cases … some examples • What auxiliary products should we recommend? • What new features should our product have? • How can we eliminate support issues?

11. Another Idea Score Your Predictive Models On Hadoop Hive UDFs Model Builder Model Description Standard Hive

13. Reinvent Your Career Lead Thrive

14. This is the time to be the river, not the rock

15. Big Data Projects on Hadoop We’re On a journey that’s just starting You Are Here….Time to get going!

16. But first! • Education • Training • Certifications

17. Hadoop Project Success Best Practice #1 • #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

18. 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)

19. Marketing The “Budget Richest” LOB? • “By 2016 the CMO will have more budget than the CIO” • - Gartner Group

21. Hadoop Project Success Best Practice#2 • #2. Use the Right Big Data Analytics tooling • Supports the entire time • Reuse and share for speed and efficiency • Leverage pre-built analytics

22. PERSONALIZED ANALYTICS HUB

23. Hadoop Project Success Best Practice#3 • #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

24. In Summary In BI, The Analyst Was at the End of the Process Ordering App Staging BI UsingData Cube Analysis Financial App Master Data • SQL Data Warehouse OLTP to OLAP Mapping • RDBS & EDW • Structured, Sampled Transitional, Closed, Expensive OLAP Reports Driven by Vendors Analyst

25. In Big Data Analytics on Hadoop The Analyst is at the Center of the Process Application Full Fidelitiy Analytics • HQL Analytics Data • HADOOP Analyst • Unstructured Behavioral, • Open, Affordable

26. Get distracted….

27. Or Big Data on Hadoop Project

28. Thank You We’re happy to help Questions