The document discusses how big data analytics are becoming more accessible and easier to use for non-experts. It outlines several trends that are making analytics more pervasive, like self-service BI tools, automated decision making, mobile apps, and analytic clouds. These trends are breaking down barriers and allowing more users at various levels to access and make sense of big data. However, expertise will still be needed to grasp big data concepts and communicate findings. The document advocates for collaborating early in projects and focusing on solving specific business problems with big data rather than viewing it as large, complex initiatives.

2. Stephen Faig
Business Development Manager
Unisphere Media
Publishers of DBTA

3. Fast and Easy Analytics:
Unlocking the Value of
Big Data Today

4. Joseph McKendrick
Lead Analyst
Unisphere Research
Suzanne L. Hoffman
Sr. Director
Tableau Software

5. Fast and Easy Analytics: Unlocking
the Value of Big Data Today
Or...
Why You
Don't Have to
be an Expert
Winemaker to
be a
Connoisseur
of Fine Wine!

6. The End of the Analytics 'Caste'
System – What It Means:
 Pervasive BI
 Automated decision making
 Unstructured or “non-traditional” data analytics
 Analytic clouds
 BI mobile apps
 Self-service BI
 Social BI

7. Pervasive BI
(Photo: US Bureau of Labor Statistics, Occupational Outlook Handbook)

8. Automated Decision Making
(Photo: Honda)

9. Unstructured or “Non-
Traditional” Data Analytics
(Photo: Fraunhofer Institute)

10. Analytic Clouds
(Photo: Joe McKendrick)

11. BI Mobile Apps
(Photo: Joe McKendrick)

12. Self-Service BI
(Photo: Stanford University)

13. Social BI
(Photo: NASA)

14. Consume Big Data Without Getting
Indigestion:
 Think About the "Last Mile" in Big Data Analytics
 Go 3D -- Even 4D! And Separate the Signal from the
Noise
 Collaborate – Early and Often
 Lead the Way
 Measure, But Don't Get too Nit-picky
 Show Me The Money! Incentivize

15. Think About the “Last Mile” in
Analytics
(Photo: Joe McKendrick)

16. Think 3D -- and Even 4D! And
Separate the Signal from the Noise
(Photo: Joe McKendrick)

17. Collaborate – Early and Often
(Photo: US Bureau of Labor Statistics, Occupational Outlook Handbook)

18. Lead the Way
(Photo: ICANN)

19. Measure, But Don't Get too
Nit-Picky

20. Show Me The Money!
Incentivize
(Photo: Joe McKendrick)

21. What it All Means
 Big data doesn't have to be big, scary projects –
start with a small, solvable business problem.
 Big data analytics should be available to all
levels of decision makers, and data needs to be
brought to life.
 Still needed: people who can grasp big data and
communicate findings to management.
 Many forms of big data will be behind-the-
scenes and invisible to end-users.

23. The Cycle ofVisual Analysis

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36. Question and Answer Session
(please submit questions)

37. Joseph McKendrick
Lead Analyst
Unisphere Research
Suzanne L. Hoffman
Sr. Director
Tableau Software

38. Please use the same URL you used to view today’s live event
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