The Briefing Room with David Loshin and OpenText Live Webcast April 14, 2015 https://bloorgroup.webex.com/bloorgroup/onstage/g.php?MTID=e079dc562543a394c5c5d0588e7cd9152 To be successful and practical in delivering meaningful insights, companies must embrace the three pillars of enterprise analytics: scalability, open standards, and speed to value. In doing so, organizations enable a range of options that can satisfy both data scientists and self-service business users alike. But getting there requires a thoughtful approach -- and some enterprise knowledge of statistical modeling. How can your company stay ahead of the game? Register for this episode of The Briefing Room to learn from veteran Analyst David Loshin, as he explains why the fundamentals will always apply to the high-stakes game of analytics. He’ll be briefed by Allen Bonde of Actuate, now part of OpenText, who will showcase his company’s intelligence platform, which was designed from the ground up to embrace open standards and was purpose-built to serve large enterprises with a wide range of data needs. He'll demonstrate recent success stories using a number of Big Data sources, including device and machine data. Visit InsideAnalysis.com for more information.

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

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Topics
April: BIG DATA
May: CLOUD
June: INNOVATORS

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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.

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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

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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.

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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

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Upcoming Topics
www.insideanalysis.com
April: BIG DATA
May: CLOUD
June: INNOVATORS

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THANK YOU
for your
ATTENTION!
Some images provided courtesy of
Wikimedia Commons