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Grab some
coffee and
enjoy the
pre-show
banter before
the top of the
hour!
The Briefing Room
Understanding What’s Possible: Getting Business Value from Big Data Quickly
Twitter Tag: #briefr The Briefing Room
Welcome
Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com
@eric_kavanagh
Twitter Tag: #briefr 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
Twitter Tag: #briefr The Briefing Room
Topics
April: BIG DATA
May: CLOUD
June: INNOVATORS
Understanding What’s Possible: Getting Business Value from Big Data Quickly
Twitter Tag: #briefr The Briefing Room
Analyst: David Loshin
David Loshin, president of Knowledge
Integrity, Inc, is a thought leader and
expert consultant in the areas of data
quality, master data management, and
business intelligence. David is the
author of numerous books and papers
on data management, including the
“Practitioner’s Guide to Data Quality
Improvement.” David is a frequent
speaker at conferences and in web
seminars. His best-selling book, “Master
Data Management,” has been endorsed
by data management industry leaders.
David can be reached at
loshin@knowledge-integrity.com, or at
(301) 754-6350.
Twitter Tag: #briefr The Briefing Room
OpenText
OpenText produces enterprise information management
software, including solutions for search, content
management and customer management
OpenText recently acquired Actuate in order to build out its
big data analytics and visualization capabilities
Actuate’s BIRT Analytics Platform includes traditional BI and
reporting, as well as advanced and predictive analytics
Twitter Tag: #briefr The Briefing Room
Guest: Allen Bonde
Allen Bonde (@abonde) is VP of Product
Marketing & Innovation at OpenText, where
he joined following the acquisition of Actuate.
A former McKinsey and Yankee Group analyst,
he was previously CMO of Offerpop, and a
Partner at Digital Clarity Group covering
social business and big data. Mr. Bonde
started his career as a data scientist in the
telecom sector, is a frequent industry speaker,
and has been featured in over 150
publications worldwide.
Twitter Tag: #briefr The Briefing Room
Perceptions & Questions
Analyst:
David Loshin
Brie%ing	
  Room:	
  
Considerations	
  for	
  
Big	
  Data	
  Analytics	
  
April	
  14,	
  2015	
  
David	
  Loshin	
  
Knowledge	
  Integrity,	
  Inc.	
  
loshin@knowledge-­‐integrity.com	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  loshin@knowledge-­‐integrity.com	
  (301)	
  754-­‐6350	
  	
   11	
  
“Big	
  Data”	
  Analytics?	
  
•  What	
  differenKates	
  “big	
  data”	
  
analyKcs	
  from	
  “regular”	
  
analyKcs?	
  
–  Scale	
  (lots	
  of	
  data)	
  
–  Scope	
  (different	
  sources)	
  
–  Speed	
  (rapid	
  Kme-­‐to-­‐value)	
  
–  Sweep	
  (lots	
  of	
  delivery	
  points)	
  
–  SoluKons	
  (addressing	
  business	
  
needs)	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
12	
  
Analytics	
  Users	
  
•  Data	
  ScienKst	
  
•  Business	
  Analyst	
  
•  IT	
  Developer	
  
•  Process	
  Owner	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
13	
  
Review	
  the	
  past	
  
Explore	
  causality	
  	
  
Consider	
  scenarios	
  
Adjust	
  behavior	
  
OpKmal	
  decisions	
  
What	
  Happened?	
   Why?	
   What	
  If?	
   How?	
  What	
  Next?	
  
Reports	
   Ad	
  Hoc	
  
Sta/s/cal	
  
Analysis	
  
Planning	
  
Forecas/ng	
  
Models	
  
Predic/ve	
  
Models	
  
Prescrip/ve	
  
Analy/cs	
  
Search	
   Dashboards	
  
Increasing	
  interest	
  in	
  more	
  complex	
  analysis	
  
Problem-­‐Solving,	
  Learning,	
  and	
  Doing	
  
•  There	
  are	
  two	
  facets	
  to	
  the	
  
analyKcs	
  process:	
  
–  Discovery	
  
–  PresentaKon	
  
•  Big	
  Data	
  AnalyKcs	
  tools	
  must	
  
facilitate	
  the	
  ways	
  the	
  
different	
  users	
  address	
  
opportuniKes	
  for	
  creaKng	
  
value	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
14	
  
IdenKfy	
  the	
  
business	
  
challenge	
  
Determine	
  
the	
  
informaKon	
  
you	
  need	
  
Discovery	
  
analysis	
  
Present	
  
results	
  
Take	
  acKon	
  
Blending	
  Different	
  Sources	
  
•  Different	
  types	
  of	
  data	
  
sources:	
  
–  Machine-­‐generated	
  content	
  
–  AutomaKcally-­‐generated	
  
content	
  
–  Human-­‐generated	
  content	
  
–  Legacy	
  content	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
15	
  
Performance	
  &	
  the	
  Extended	
  Enterprise	
  
•  The	
  organizaKon’s	
  data	
  
resources	
  expand	
  beyond	
  the	
  
administraKve	
  boundaries	
  
–  Cloud-­‐based	
  applicaKons	
  
–  Hosted	
  systems	
  
–  Sensors	
  
–  Human-­‐generated	
  media	
  
–  Mobile	
  devices	
  
•  Performance	
  is	
  criKcal	
  to	
  
deliver	
  acKonable	
  knowledge	
  
within	
  the	
  window	
  of	
  
opportunity	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
16	
  
Questions	
  
•  Can	
  you	
  describe	
  some	
  of	
  the	
  enhancements	
  you	
  have	
  undertaken	
  to	
  
improve	
  performance	
  across	
  the	
  extended	
  enterprise?	
  
•  Data	
  scienKsts	
  with	
  staKsKcal	
  backgrounds	
  are	
  very	
  different	
  than	
  casual	
  
business	
  users.	
  How	
  does	
  the	
  product	
  saKsfy	
  the	
  needs	
  of	
  the	
  different	
  
types	
  of	
  users?	
  
•  What	
  are	
  the	
  disKncKve	
  features	
  of	
  the	
  product	
  that	
  facilitate	
  the	
  
“understand”	
  process?	
  
•  How	
  can	
  the	
  product	
  suite	
  train	
  users	
  to	
  become	
  more	
  adept	
  at	
  both	
  the	
  
“understand”	
  and	
  “engage”	
  phases	
  of	
  the	
  analyKcs	
  process?	
  
•  The	
  Apple	
  Watch	
  is	
  one	
  of	
  the	
  recently	
  announced	
  wearable	
  devices.	
  How	
  
does	
  the	
  “wearable”	
  paradigm	
  impact	
  your	
  plans	
  for	
  big	
  data	
  analyKcs?	
  
•  Speaking	
  of	
  the	
  wearables,	
  what	
  thoughts	
  do	
  you	
  have	
  about	
  adapKng	
  to	
  
non-­‐convenKonal	
  methods	
  of	
  knowledge	
  delivery?	
  And	
  data	
  acquisiKon?	
  
•  What	
  opportuniKes	
  are	
  there	
  for	
  pushing	
  analyKcs	
  to	
  the	
  middle	
  and	
  
edges	
  of	
  the	
  extended	
  enterprise?	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
17	
  
Stay	
  in	
  Touch	
  
•  www.knowledge-­‐integrity.com	
  
•  www.dataqualitybook.com	
  
•  www.decisionworx.com	
  
•  If	
  you	
  have	
  quesKons,	
  comments,	
  
or	
  suggesKons,	
  please	
  contact	
  me	
  
David	
  Loshin	
  
301-­‐754-­‐6350	
  
loshin@knowledge-­‐integrity.com	
  
©	
  2015	
  Knowledge	
  Integrity,	
  Inc	
  
loshin@knowledge-­‐integrity.com	
  
(301)	
  754-­‐6350	
  
18	
  
Twitter Tag: #briefr The Briefing Room
Twitter Tag: #briefr The Briefing Room
Upcoming Topics
www.insideanalysis.com
April: BIG DATA
May: CLOUD
June: INNOVATORS
Twitter Tag: #briefr The Briefing Room
THANK YOU
for your
ATTENTION!
Some images provided courtesy of
Wikimedia Commons

More Related Content

Understanding What’s Possible: Getting Business Value from Big Data Quickly

  • 1. Grab some coffee and enjoy the pre-show banter before the top of the hour!
  • 2. The Briefing Room Understanding What’s Possible: Getting Business Value from Big Data Quickly
  • 3. Twitter Tag: #briefr The Briefing Room Welcome Host: Eric Kavanagh eric.kavanagh@bloorgroup.com @eric_kavanagh
  • 4. Twitter Tag: #briefr 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
  • 5. Twitter Tag: #briefr The Briefing Room Topics April: BIG DATA May: CLOUD June: INNOVATORS
  • 7. Twitter Tag: #briefr The Briefing Room Analyst: David Loshin David Loshin, president of Knowledge Integrity, Inc, is a thought leader and expert consultant in the areas of data quality, master data management, and business intelligence. David is the author of numerous books and papers on data management, including the “Practitioner’s Guide to Data Quality Improvement.” David is a frequent speaker at conferences and in web seminars. His best-selling book, “Master Data Management,” has been endorsed by data management industry leaders. David can be reached at loshin@knowledge-integrity.com, or at (301) 754-6350.
  • 8. Twitter Tag: #briefr The Briefing Room OpenText OpenText produces enterprise information management software, including solutions for search, content management and customer management OpenText recently acquired Actuate in order to build out its big data analytics and visualization capabilities Actuate’s BIRT Analytics Platform includes traditional BI and reporting, as well as advanced and predictive analytics
  • 9. Twitter Tag: #briefr The Briefing Room Guest: Allen Bonde Allen Bonde (@abonde) is VP of Product Marketing & Innovation at OpenText, where he joined following the acquisition of Actuate. A former McKinsey and Yankee Group analyst, he was previously CMO of Offerpop, and a Partner at Digital Clarity Group covering social business and big data. Mr. Bonde started his career as a data scientist in the telecom sector, is a frequent industry speaker, and has been featured in over 150 publications worldwide.
  • 10. Twitter Tag: #briefr The Briefing Room Perceptions & Questions Analyst: David Loshin
  • 11. Brie%ing  Room:   Considerations  for   Big  Data  Analytics   April  14,  2015   David  Loshin   Knowledge  Integrity,  Inc.   loshin@knowledge-­‐integrity.com   ©  2015  Knowledge  Integrity,  Inc  loshin@knowledge-­‐integrity.com  (301)  754-­‐6350     11  
  • 12. “Big  Data”  Analytics?   •  What  differenKates  “big  data”   analyKcs  from  “regular”   analyKcs?   –  Scale  (lots  of  data)   –  Scope  (different  sources)   –  Speed  (rapid  Kme-­‐to-­‐value)   –  Sweep  (lots  of  delivery  points)   –  SoluKons  (addressing  business   needs)   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   12  
  • 13. Analytics  Users   •  Data  ScienKst   •  Business  Analyst   •  IT  Developer   •  Process  Owner   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   13   Review  the  past   Explore  causality     Consider  scenarios   Adjust  behavior   OpKmal  decisions   What  Happened?   Why?   What  If?   How?  What  Next?   Reports   Ad  Hoc   Sta/s/cal   Analysis   Planning   Forecas/ng   Models   Predic/ve   Models   Prescrip/ve   Analy/cs   Search   Dashboards   Increasing  interest  in  more  complex  analysis  
  • 14. Problem-­‐Solving,  Learning,  and  Doing   •  There  are  two  facets  to  the   analyKcs  process:   –  Discovery   –  PresentaKon   •  Big  Data  AnalyKcs  tools  must   facilitate  the  ways  the   different  users  address   opportuniKes  for  creaKng   value   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   14   IdenKfy  the   business   challenge   Determine   the   informaKon   you  need   Discovery   analysis   Present   results   Take  acKon  
  • 15. Blending  Different  Sources   •  Different  types  of  data   sources:   –  Machine-­‐generated  content   –  AutomaKcally-­‐generated   content   –  Human-­‐generated  content   –  Legacy  content   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   15  
  • 16. Performance  &  the  Extended  Enterprise   •  The  organizaKon’s  data   resources  expand  beyond  the   administraKve  boundaries   –  Cloud-­‐based  applicaKons   –  Hosted  systems   –  Sensors   –  Human-­‐generated  media   –  Mobile  devices   •  Performance  is  criKcal  to   deliver  acKonable  knowledge   within  the  window  of   opportunity   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   16  
  • 17. Questions   •  Can  you  describe  some  of  the  enhancements  you  have  undertaken  to   improve  performance  across  the  extended  enterprise?   •  Data  scienKsts  with  staKsKcal  backgrounds  are  very  different  than  casual   business  users.  How  does  the  product  saKsfy  the  needs  of  the  different   types  of  users?   •  What  are  the  disKncKve  features  of  the  product  that  facilitate  the   “understand”  process?   •  How  can  the  product  suite  train  users  to  become  more  adept  at  both  the   “understand”  and  “engage”  phases  of  the  analyKcs  process?   •  The  Apple  Watch  is  one  of  the  recently  announced  wearable  devices.  How   does  the  “wearable”  paradigm  impact  your  plans  for  big  data  analyKcs?   •  Speaking  of  the  wearables,  what  thoughts  do  you  have  about  adapKng  to   non-­‐convenKonal  methods  of  knowledge  delivery?  And  data  acquisiKon?   •  What  opportuniKes  are  there  for  pushing  analyKcs  to  the  middle  and   edges  of  the  extended  enterprise?   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   17  
  • 18. Stay  in  Touch   •  www.knowledge-­‐integrity.com   •  www.dataqualitybook.com   •  www.decisionworx.com   •  If  you  have  quesKons,  comments,   or  suggesKons,  please  contact  me   David  Loshin   301-­‐754-­‐6350   loshin@knowledge-­‐integrity.com   ©  2015  Knowledge  Integrity,  Inc   loshin@knowledge-­‐integrity.com   (301)  754-­‐6350   18  
  • 19. Twitter Tag: #briefr The Briefing Room
  • 20. Twitter Tag: #briefr The Briefing Room Upcoming Topics www.insideanalysis.com April: BIG DATA May: CLOUD June: INNOVATORS
  • 21. Twitter Tag: #briefr The Briefing Room THANK YOU for your ATTENTION! Some images provided courtesy of Wikimedia Commons