2. > Agenda
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3. > Hadoop not standing alone

4. > Parallel and Complementary Stacks

5. > The Best of Both Worlds = Big Data Analytics + Traditional BI

6. > Big Data Analytics on Hadoop Use Cases
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7. > What Hadoop Adopters Are Saying

8. > How to make Hadoop successful with BI

9. > Cornerstone 1: Employ All Data
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• Raw unstructured – Web logs, machine
/sensor data, mobile social, video, etc.
• Structured data – traditional RDMBS, EDW’s
• Streaming vs. batch oriented
• Data governance and quality

10. > Cornerstone 2: Use All Analytic Assets
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• Traditional models and assets
• Standard Hadoop components including
UDFs and SerDes
• Custom algorithms
• Models created in other systems such as
SAS/R

11. > Cornerstone 3: Provide Self-Service Access for All Users
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• Easy-to-use ad-hoc analysis, web-based forms
• Drag and drop
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• Common skills: SQL
• Powerful iterative analysis
• Analytical models and algorithms
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12. > Cornerstone 4: Build a Collaborative Environment
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• Metadata, Queries, Results and Visualizations
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13. > Cornerstone 5: Be Open and Extensible
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14. > Cornerstone 6: Populate Best-of-Breed Reporting Tools
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15. > How would an architecture look

16. > Summary

17. > Summary Get the Best of Both Worlds – Build a Bridge Inside Your Company
Big Data Analytics on Hadoop
Future, see intent
Drives Optimization
BI Just getting started
Historical
Drives reporting
Entrenched
Be around for a long time

18. abetaha@karmasphere.com
www.karmasphere.com