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Karmasphere bdabi blueprint- final
> Agenda







> Hadoop not standing alone
> Parallel and Complementary Stacks
> The Best of Both Worlds = Big Data Analytics + Traditional BI
> Big Data Analytics on Hadoop Use Cases




               •
               •
               •



               •
               •
               •



               •
               •
               •
> What Hadoop Adopters Are Saying
> How to make Hadoop successful with BI
> Cornerstone 1: Employ All Data




    •   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
> Cornerstone 2: Use All Analytic Assets




    •   Traditional models and assets

    •   Standard Hadoop components including
        UDFs and SerDes

    •   Custom algorithms

    •   Models created in other systems such as
        SAS/R
> Cornerstone 3: Provide Self-Service Access for All Users




•
•
•


•
    •   Easy-to-use ad-hoc analysis, web-based forms
    •   Drag and drop

•
    •   Common skills: SQL
    •   Powerful iterative analysis
    •   Analytical models and algorithms

•
> Cornerstone 4: Build a Collaborative Environment




•

•

•


•
    •   Metadata, Queries, Results and Visualizations

•

•
> Cornerstone 5: Be Open and Extensible




•

•

•

•

•



•

•

•
>   Cornerstone 6: Populate Best-of-Breed Reporting Tools




•


•

•

•
> How would an architecture look
> Summary
> 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
abetaha@karmasphere.com
www.karmasphere.com

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Karmasphere bdabi blueprint- final

  • 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 • • • • • • • • •
  • 7. > What Hadoop Adopters Are Saying
  • 8. > How to make Hadoop successful with BI
  • 9. > Cornerstone 1: Employ All Data  • 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  • 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  • • •  • • Easy-to-use ad-hoc analysis, web-based forms • Drag and drop • • Common skills: SQL • Powerful iterative analysis • Analytical models and algorithms •
  • 12. > Cornerstone 4: Build a Collaborative Environment  • • •  • • Metadata, Queries, Results and Visualizations • •
  • 13. > Cornerstone 5: Be Open and Extensible  • • • • •  • • •
  • 14. > Cornerstone 6: Populate Best-of-Breed Reporting Tools  • • • •
  • 15. > How would an architecture look
  • 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

Editor's Notes

  1. One large chip manufacture
  2. Co-existence
  3. Final