Get Smart: The Present and Future of Data Discovery

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Hot Technologies of 2013 with Bloor, Fitzgerald & Neutrino BI
Live Webcast July 17, 2013
http://www.insideanalysis.com

Somewhere in your data, discoveries wait to be found. Finding them can be quite a challenge, though, which is why data discovery gets so much attention these days. A whole array of tools is being promoted for data visualization and business discovery. But what are the component parts of this technology? And how can discovery tools be used to sift through vast amounts of data effectively? Register for this episode of Hot Technologies to find out!

Analysts Dr. Robin Bloor of The Bloor Group, and Jaime Fitzgerald of Fitzgerald Analytics will each offer their take on what constitutes a high-quality discovery tool. They'll then take a briefing from Jon Woodward of Neutrino BI, who will tout his company's platform for facilitating data discovery. He'll talk about the value of being able to go "direct to data" during the discovery process. He'll also outline their roadmap for developing a next-generation "smart" discovery platform.

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Get Smart: The Present and Future of Data Discovery

  1. 1. H T  Technologies   2013  
  2. 2. HOST:   Eric  Kavanagh  
  3. 3.      THIS  YEAR  is…  
  4. 4. Data  Discovery   ž  Data  discovery  provides  visibility  into  enterprise   information  assets   ž  Good  data  discovery  delivers  intelligence  and   insight,  and  great  data  discovery  enables  action   ž  People  process  information  visually—it  makes   sense  to  use  a  BI  tool  that  naturally  follows  the   visual  train  of  thought  
  5. 5. ANALYST:   Jaime  Fitzgerald   Founder  &  President,  Fitzgerald  Analytics   ANALYST:   Robin  Bloor   Chief  Analyst,  The  Bloor  Group   GUEST:   Jon  Woodward   CEO,  Neutrino  BI   THE  LINE  UP  
  6. 6. INTRODUCING   Jaime  Fitzgerald   Architects  of  Fact-­‐Based  Decisions™  
  7. 7. Data  Discovery  for  Big  Insights     Jaime  Fitzgerald   Founder  &  Managing  Partner,  Fitzgerald  Analy?cs     July  17,  2013   Architects  of  Fact-­‐Based  Decisions™  
  8. 8. 8  Data  Discovery  for  Big  Insights                  ©  2013  Fitzgerald  Analy>cs,  Inc.  All  Rights  Reserved   Nice  to  meet  you,  I’m  Jaime  Fitzgerald   Transforming  data  into  dollars  for  17  years   Founded  Fitzgerald  Analy?cs  in  2005   TwiJer:  @jaimefitzgerald  @fitzanaly?cs   Hashtag:  #D2DVC   Focus   § Created  Data  to  Dollars  Value  Chain™  framework.       § Author  of  book  on  the  methodology     Pub  date:  early  ‘14  via  Morgan  Kaufmann     Making  it  Easier  to  Find  Opportuni?es   to  turn  Data  into  Results….       ….and  BeJer  Ways  to    Unlock  That  Poten?al     Results     so  Far  
  9. 9. 9  Data  Discovery  for  Big  Insights                  ©  2013  Fitzgerald  Analy>cs,  Inc.  All  Rights  Reserved   If  “Data  is  the  New  Oil,”  how  do  we  use  it  well?*     *first  included  in  a  report  from  the  World  Economic  Forum,  the  phrase  ““Data  is  the  New  Oil”    has  since   been  used  widely,  in  both  realis>c  and  unrealis>c  ways.  
  10. 10. 10  Data  Discovery  for  Big  Insights                  ©  2013  Fitzgerald  Analy>cs,  Inc.  All  Rights  Reserved   §  New  Data   Source   Acquisi>on   §  Data  Discovery     §  Data  Quality   §  Data   Governance     Analysis   Insight   §  Decisions   §  Ac>ons   §  Financial  Impact   §  New  Data   §  New   Opportuni>es   Visualizing  the  Process   3.  Results     2.  Analysis     1.  Data     The  Data  to  Dollars  Value  Chain™   Naviga?on   Tips:     1.  Avoid  Linearity   (loop  back  oden)   2.  Stay  Agile   3.  Keep  Oriented   (“line  of  sight”  /   “why  am  I  doing   this?)  
  11. 11. 11  Data  Discovery  for  Big  Insights                  ©  2013  Fitzgerald  Analy>cs,  Inc.  All  Rights  Reserved   Salient  Trends  in  Data  Discovery   Trend   Implica?on   1.  Agile  Analy?cs   Users  need  more  flexible  &  efficient  tools  for  rapid-­‐cycle,   itera>ve  analysis   2.  Big  Data   More  data,  in  a  variety  of  formats,  is  available  and  needs  to   be  profiled,  processed,  integrated,  and  used  appropriately   3.  Data  Visualiza?on   Today’s  execu>ves,  managers,  and  analysts  expect  insights   to  be  delivered  visually.    Data  visualiza>on  has  gone  from   “nice  to  have”  to  “expected.”  
  12. 12. 12  Data  Discovery  for  Big  Insights                  ©  2013  Fitzgerald  Analy>cs,  Inc.  All  Rights  Reserved   Key  Success  Factors   1.  “Begin  with  the  End  in  Mind”    (Goal-­‐Centricity)     2.   Agility  &  Fast  Itera?on     3.  Take  advantage  of  BOTH     1.  “Known  Unknowns”  and   2.  “Unknown  Unknowns”   4.  Cross-­‐Func?onal  Collabora?on  (IT,  Data,   Business,  Domain  Experts)  
  13. 13. INTRODUCING   Robin  Bloor  
  14. 14. A NEW UNIVERSE OF BI?The Self-Service Dynamic The Expertise of the BI User
  15. 15. The Future of BI •  End-to-end: from data access to usage •  Performance/timeliness (overall) •  Self-service The Next Generation of BI is based on:
  16. 16. Self-Service Issues •  Governance & Approval •  Data self-service •  Skills •  Actual efficiency
  17. 17. Self-service & Productivity The level of self-service, and its usefulness, is not a simple thing. In the BEST of circumstances the user probably cannot self-design the way their whole job works, so EASE-OF-USE and FLEXIBILITY count.
  18. 18. BI: Of the User, By the User, For the User The issues in summary: Data flow integration/ automation Performance/ timeliness (overall) Data coverage: data sources, also structured/ unstructured data Data cleansing Data access skills Shareability ActionabilityVisualizations
  19. 19. Image credit on Slide 2: mhbphoto /123RF Stock Photo Thank You Robin Bloor Robin.Bloor@bloorgroup.com www.bloorgroup.com
  20. 20. INTRODUCING   Jon  Woodward  
  21. 21. Smart  Data  Discovery   The  next  step  in  visual  analy>cs  &  data  discovery   Jon  Woodward,  CEO,  NeutrinoBI  
  22. 22. July  16,  2013              |   Slide  22   Since  1958…  the  quest  for  answers   Database  &     Data  Warehouse   Repor?ng   OLAP   Visual  Data     Discovery   Mobile     SMART  Predic?ve   Big  data  Data  silos  Complex  fabric   Mul>ple  devices   1960   1980   2010   2013  
  23. 23. July  16,  2013              |   Slide  23   What  are  we  searching  for?   A  tool  that  will  allow  ANYONE  to…    Ask  the  RIGHT  QUESTION    Get  insights  that  are  RIGHT  FOR  THEM    At  the  RIGHT  TIME  to  impact  today’s  decision        Ac?onable  insight    
  24. 24. July  16,  2013              |   Slide  24   Are  we  nearly  there  yet?   •  S>ll  a  long-­‐way  from  pervasive  BI   –  adop?on  remains  at  24%   •  1st  genera>on  data  discovery   tools  are  s?ll  difficult  to  use   •  Applica>ons  must  be  built,   constrained  by  today’s  thinking   •  Designed  as  ‘one-­‐size  fits  all’   Data  Discovery   Dashboards   Predic>ve   analy>cs   KPI  Alerts  Some  limited   collabora?on   Faceted  search   In-­‐memory   Mobile  BI   We’re  s>ll  falling  short  of  Smart  Data  Discovery  
  25. 25. July  16,  2013              |   Slide  25   What  would  Smart  Data  Discovery  look  like?   “Tell  me  more  about…”     “What’s  the  stock  price  of…”   “How  many  units  of  Widget  Y   were  sold  yesterday?...”     “Good  morning  –  the  key   alerts  for  your  aoen>on   today  are…”  
  26. 26. July  16,  2013              |   Slide  26   What  are  the  components  of  a  smart  tool?   Ability  to  ask     any  ques?on   Beau?ful,  clear   visual  answers   Con>nuously  learn  from   ques>ons  &  answers  
  27. 27. July  16,  2013              |   Slide  27   What  should   Ques>on  look  like?       Allow  you  to  ask  any   way  you  want   • Voice  or  touch   • Text  or  type     Understand  what  you  mean   • Context   • Loca>on   Provide  a  universe  of   intelligence  to  draw  from   • Big  data  just  another  source   • Real  >me,  anywhere    
  28. 28. July  16,  2013              |   Slide  28   What  difference  could   Learn  make?   Ask   help  you  to  refine   your  ques>on   Observe   the  context   you’re  asking  from   Listen   and  take  note  of  the   Ques>ons  being  asked   Expand   the  picture  with   Insight  from  your   social  network   Alert   you  to  when  answers   have  changed   Be  proac?ve   serve  up  insight  based  on   what  you’ve  been  asking  
  29. 29. July  16,  2013              |   Slide  29   What  does  a   Beau>ful  interface  look  like?   Consistent   Immersive   Op>mised  
  30. 30. July  16,  2013              |   Slide  30   All  of  this  AND…   The  smart  BI  tool  wouldn’t  need   you  to  build  an  applicaBon   interface,  or  invest  in  further   development  every  Bme  the  world   of  your  data  discovery  changed.  
  31. 31. July  16,  2013              |   Slide  31   Introducing  NeutrinoBI  
  32. 32. July  16,  2013              |   Slide  32   Just  ask!  
  33. 33. July  16,  2013              |   Slide  33   Interact  &  Share  
  34. 34. July  16,  2013              |   Slide  34   Search,  discover,  share…any>me  &  anywhere  
  35. 35. July  16,  2013              |   Slide  35   No  applica>on  development  =  rapid  implementa>on  
  36. 36. July  16,  2013              |   Slide  36   How  long  do  I  have  to  wait  for  Smart  Data  Discovery?  
  37. 37. July  16,  2013              |   Slide  37   Next  steps…   Visit   www.neutrinobi.com     To  learn  more  about     NeutrinoBI:   Request  a  live  demo   webinar  email:   demo@neutrinobi.com     See  NeutrinoBI  in  ac>on   For  POC  in  less  than  a   day,  email:   poc@neutrinobi.com   Discover  the  benefits  of   NeutrinoBI  on  your  data    
  38. 38. July  16,  2013              |   Slide  38   Accelerate  your  discoveries  
  39. 39. The  Archive  Trifecta:   •  Inside  Analysis    www.insideanalysis.com   •  SlideShare    www.slideshare.net/InsideAnalysis   •  YouTube    www.youtube.com/user/BloorGroup   THANK  YOU!  

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