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The Briefing Room

Connecting the Dots with Data Mashups

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The Briefing Room

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The Briefing Room

Welcome

Host: Eric Kavanagh

[email protected]

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The Briefing Room

!   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!

Mission

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JANUARY: Big Data

February: Analytics

March: Open Source

April: Intelligence

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The Briefing Room

Big Data

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COMBINING DATA

GLEANING INSIGHTS FINDING MEANINGFUL DATA SETS

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Analyst: Lyndsay Wise

Lyndsay Wise is the president and founder of WiseAnalytics, a boutique analyst and consultancy firm. Lyndsay has ten years of IT experience in business systems analysis, software selection, and implementation of enterprise applications. She provides consulting services for small and mid-sized companies and conducts research into leading technologies, market trends, BI products and vendors, mid-market needs, and data visualization.

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!   Tableau builds software for data visualization, business intelligence and analytics

!   Their stated mission is to help people see and understand data

!   Its platform is designed for ease of use by both power and casual users

Tableau Software

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Ellie Fields

Ellie Fields is the Director of Product Marketing at Tableau Software. She has spoken at numerous industry events for business intelligence as well as for data journalism. Prior to Tableau, Ellie worked at Microsoft and in late-stage venture capital. Ellie is a graduate of Rice University and the Stanford Graduate School of Business.

Connecting the Dots

Ellie Fields Senior Director, Tableau Software

@eleanorpd

Then: Big data everywhere, various data stores, data stuck and no insight – billions of rows of data.

Now: Centralized view into data across the organization.

Analytics to drive the site.

Then: Doctors, nurses, all staff want to use data to improve

the quality of service.

Now: Self service reporting for everyone. 800+ people using multiple sources of data to answer questions.

The Problem: Volume of Data Businesses are struggling to unlock exploding data

The Problem: Diverse Data Businesses and their people are struggling to unlock diverse data

The Problem: Old School Software Traditional technologies are complicated, inflexible and slow moving

What Happens in the Real World

Faster Rapidly unlock data, even big data, and gain on-time insight

Flexible Transform all types of data into self-service analytics

For Everyone Ease of use leads to adoption across all departments and use cases

Customers 10,000 customers from every industry and geography

DEMO

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Analyst: Lyndsay Wise

Perceptions & Questions

Big  Data  -­‐  Then      

Etc….  

Consolida6ng  and  managing  distributed  and  large  data  sets  

Big  Data  Now  

Data  Warehouse  

Added  Valu  OLAP   Dashboards   Reports  

Added  Value  

Value  From  Big  Data  

From  Management  To  Insight  

•  Managing  big  data  infrastructures  are  no  longer  enough  

•  Organiza6ons  require  a  way  to  get  value  out  of  their  data  

•  Evalua6ng  BI  on  its  merit  in  rela6on  to  big  data  management  is  becoming  a  must  have  for  many  businesses  

Ques6ons  

•  Big  data  is  defined  a  variety  of  ways  in  the  industry  today  –  what  is  Tableau’s  sweet  spot  within  big  data  analy6cs?  Does  it  extend  beyond  diversity  and  volume?  

•  The  two  examples  you  used  focus  on  data  consolida6on  and  self-­‐service  access  for  hundreds  (if  not  thousands)  of  people.  How  are  other  companies  using  Tableau  to  address  their  big  data  challenges?  

Ques6ons  

•  What  is  the  real  differen6ator/value  proposi6on  in  comparison  to  how  other  similar  vendors  address  big  data  challenges?  

•  When  would  a  company  not  want  to  use  Tableau  to  manage  their  big  data?  

•  How  does  Tableau  provide  faster  data  access  (slide  11  reference)?  Do  limita6ons  exist,  i.e.,  does  this  depend  on  the  plaZorm,  etc.?  

Ques6ons  

•  What  limita6ons  exist  in  rela6on  to  data  volumes  or  added  complexi6es?  

•  What  trends  do  you  see  in  rela6ons  to  customer  use  and  the  transi6on  from  big  data  storage  to  big  data  analy6cs?  

•  For  organiza6ons  evalua6ng  Tableau  for  big  data  access,  what  do  they  need  to  know  or  prepare  in  advance  to  get  the  system  up  and  running?  

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Upcoming Topics

This month: Big Data

February: Analytics

March: Open Source

April: Intelligence

www.insideanalysis.com

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Thank You for Your

Attention