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The Formula for Hadoop Project Success Gail Ennis CEO.

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Presentation on theme: "The Formula for Hadoop Project Success Gail Ennis CEO."— Presentation transcript:

1 The Formula for Hadoop Project Success Gail Ennis CEO

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

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4 InformationWeek 2013 There’s certainly challenges

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

6

7 Big Data Analytics

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

9 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

10

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

12

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 #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

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

20

21 #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

22 PERSONALIZED ANALYTICS HUB

23 #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

24 Data Warehouse OLTP to OLAP Mapping 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 SQLSQLSQLSQL Driven by Vendors

25 In Big Data Analytics on Hadoop The Analyst is at the Center of the Process ApplicationApplication Analytics Data Unstructured Behavioral, Open, Affordable HADOOP HQLHQLHQLHQL Analyst Full Fidelitiy Analytics

26 Get distracted….

27 Or Big Data on Hadoop Project

28 Thank You We’re happy to help Questions


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