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Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
Big Data Analytics: Gleaning Insights with Data Discovery
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Big Data Analytics: Gleaning Insights with Data Discovery

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The Briefing Room with Robin Bloor and Tableau Software …

The Briefing Room with Robin Bloor and Tableau Software
Slides from the Live Webcast on Apr. 24, 2012

While data volumes and varieties continue to expand, so do the ways in which businesses can analyze and leverage their information assets. The increased number of available dimensions tends to complicate the analytical process, however. That's where data discovery plays an invaluable role, both for Big Data and traditional business analytics. When information workers are empowered to explore these diverse data sets freely, valuable insights tend to materialize.

In this episode of The Briefing Room, Analyst Robin Bloor explains how data discovery can help reveal significant patterns that can help any organization. He'll walk through the discovery process, starting with the identification of key dimensions, then moving into the visualization and discovery stage. Bloor will be briefed by Ellie Fields of Tableau Software, who will demonstrate how a variety of data sets and attributes can be quickly mixed and matched to create new and thought-provoking views of business opportunities.

For more information visit: http://www.insideanalysis.com

Watch us on YouTube: http://www.youtube.com/playlist?list=PL5EE76E2EEEC8CF9E

Published in: Technology, Education
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Transcript

  • 1. Tuesday, April 24, 12
  • 2. Eric.kavanagh@bloorgroup.com Twitter Tag: #briefrTuesday, April 24, 12
  • 3. Reveal the essential characteristics of enterprise software, good and bad Provide a forum for detailed analysis of today’s innovative technologies Give vendors a chance to explain their product to savvy analysts Allow audience members to pose serious questions... and get answers! Twitter Tag: #briefrTuesday, April 24, 12
  • 4. April: Discovery May: Analytics June: Intelligence July: Governance August: Analytics Twitter Tag: #briefrTuesday, April 24, 12
  • 5. BI and Analytics appears to be changing rapidly. This may partly be because traditional BI technology (reporting, dashboards, OLAP) is now well entrenched and serving its purpose. Big data and data integration technologies have conspired together to provide new aggregations and sources of data to explore. Open source technologies, (Hadoop. Hive, Hbase, Pig etc.) in conjunction with the cloud have considerably reduced the price of leveraging new and, often very substantial data sources. On the desktop, BI users now have data discovery capabilities that they once only dreamed of. Twitter Tag: #briefrTuesday, April 24, 12
  • 6. Robin Bloor is Chief Analyst at The Bloor Group. Robin.Bloor@Bloorgroup.com Twitter Tag: #briefrTuesday, April 24, 12
  • 7. Tableau builds software for data visualization and rapid-fire business intelligence. The mission: help people see and understand data. Tableau delivers excellent visualization and offers a wide variety of data representation possibilities. It is a BI platform that fits both power users and normal BI users and now, with Tableau 6.1 it is enabled for iPad use. No extra effort is required to deliver Tableau reports to the iPad Twitter Tag: #briefrTuesday, April 24, 12
  • 8. Ellie Fields is the Director of Product Marketing at Tableau Software. She is responsible for developing market requirements, performing customer research and managing product launches. She has spoken at numerous industry events for business intelligence as well as for data journalism.Prior to Tableau, Ellie worked at Microsoft and as an associate in late-stage venture capital. Ellie holds B.S. and B.A. degrees from Rice University and an MBA from the Stanford Graduate School of Business. Twitter Tag: #briefrTuesday, April 24, 12
  • 9. Ellie%Fields%Senior%Director,%Tableau%So5ware% Twi7er:%eleanorpd%Data Discovery All#rights#reserved.#©#2008#Tableau#So8ware#Inc.#
  • 10. AgendaWhat is Data Discovery?3 Things You Need for Data DiscoveryDemo
  • 11. What is DataDiscovery?
  • 12. No Yes•  Regular dashboards •  Cycle of analysis•  Established metrics •  Many unknowns•  “Specialist” approach •  Self-service
  • 13. Data Discovery Involves... Disparate Data Big(gish) Data New Data …otherwise it wouldn’t be necessary
  • 14. Disparate Data Cubes Data Files Warehouse Files Data MartsThe organization that has all its data in one place does not exist.
  • 15. New DataNew behaviorsOur customers are changing what theybuy online.New goalsWe’re expanding into new markets.New competitionNew technology and new entrants arechanging our markets.
  • 16. Big Data … and getting bigger every day. Product managers routinely work with “tens of millions to a few hundred millions of rows”“Four billion impressions of ad serving data come into ourdatabase every day. We have the largest multi-dimensionaldatabase in the world that Tableau’s running on.”
  • 17. 3 Things YouNeed for DataDiscovery
  • 18. 1 The freedom to choose2 Data blending3 Self-service, rapid iterative approach
  • 19. The Freedom to Choose
  • 20. Tableau’s Data Engine•  In-memory solution in 1 click•  Removes load from production databases•  Refresh anytime or schedule updates•  Incremental refresh•  Switch to live connect as needed
  • 21. Data Blending
  • 22. Self-Service with Rapid Iterations click click
  • 23. DEMO
  • 24. Twitter Tag: #briefrTuesday, April 24, 12
  • 25. Tuesday, April 24, 12
  • 26. “The voyage of discovery is not in seeking new landscapes, but in having new eyes.” Marcel Proust In BI, I prefer the idea of both new landscapes and new eyesTuesday, April 24, 12
  • 27. Tuesday, April 24, 12
  • 28. Tuesday, April 24, 12
  • 29. Twitter Tag: #briefrTuesday, April 24, 12
  • 30. The Impact BI processes can be: More convenient Be applied to new areas Accelerated Change in their nature Lead to unanticipated results: (Discovery begets discovery) Twitter Tag: #briefrTuesday, April 24, 12
  • 31. Questions Using Tableau, how much data can an individual manage within a personal database What are Tableau’s capabilities in the following areas: Standard BI (reporting, dashboards, etc.) OLAP Analytics Discovery What are Tableau’s dependencies in respect of data service? (i.e. what is necessary? what is desirable?) Are there any specific technology partnerships that Tableau has? If so, then with whom and what’s the pay-off? Twitter Tag: #briefrTuesday, April 24, 12
  • 32. Questions Is Tableau complementary to or a replacement for spreadsheet BI? How (in Tableau’s experience) does the expansion of the global data space alter what users do with their capability? How (in Tableau’s experience) do improved speeds of iteration affect the analytical process? Is there a developing community of “Power Users” of Tableau? Who have been the early adopters of this kind of capability and what kind of business problems are they trying to solve? Which vertical business sectors have shown most interest and which have shown least interest? Twitter Tag: #briefrTuesday, April 24, 12
  • 33. Tuesday, April 24, 12
  • 34. May: Analytics • June: Intelligence • July: Governance • August: Analytics Twitter Tag: #briefrTuesday, April 24, 12
  • 35. Tuesday, April 24, 12

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