The Briefing Room with Dr. Robin Bloor and IBM Business Analytics
Live Webcast Oct. 29, 2013
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?AT=pb&SP=EC&rID=7691327&rKey=cd0c2bf8140ac684
You know that a-ha moment--when you discover that key business insight. That special moment often occurs when you design an effective data visualization. The obvious challenge is that doing so usually requires far more than a pie chart. Luckily, there's something of a revolution happening in the field of data visualization. Thanks to the powers of standards and collaboration, the variety of data visualizations available to information workers is at an all-time high.
Register for this episode of The Briefing Room to learn from veteran Analyst Dr. Robin Bloor, who will explain why a proliferation of new data visualization options is fundamentally changing the way analytics deliver value. He'll be briefed by Noah Iliinsky of IBM, who will tout his company's new extensible visualization capabilities, which give end users access to an ever-growing library of data visualizations. He'll also discuss his four pillars for effective visualizations, and how professionals can use them to create lasting impact.
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3. Mission
! 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!
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5. Data Visualization
“
Learning
is
more
effec.ve
when
it
is
an
ac.ve
rather
than
a
passive
process.
~Euripides
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6. Analyst: Robin Bloor
Robin Bloor is
Chief Analyst at
The Bloor Group
robin.bloor@bloorgroup.com
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7. IBM
! IBM Business Analytics offers a wide range of business
intelligence, analytics and performance management
solutions
! Many Eyes, powered by the IBM Rapidly Adaptive
Visualization Engine (RAVE), is a web community that helps
users create advanced visualizations from public data sets
! Visualizations can be shared and embedded
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8. Guest: Noah Iliinski
Noah Iliinski,
Visualization Expert
at IBM
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43. Tables and Dimensions
The problems with“unvisualized” data:
u Every
u Time
column in a table is a dimension
is a critical dimension
u Some
dimensions have high variability (say 00.00
to 1,000,000.00), others low variability (male/
female), others are descriptors or UIDs
u A
table is possibly the worst way to represent
data helpfully – although you can do things with
a table (counts, averages, etc.)
u It’s
a very good way to store data
44. Information Service
There are many reasons why data may be provided to
people:
u To
inform or alert them
u To
motivate them
u To
entertain them
u To
assist them (assist decisions)
u To
empower them (or evaluate them?)
u To
educate them (or help them self-educate)
THE CONTEXT DETERMINES THE INFORMATION SERVICE
AND ITS CHARACTER
45. Consumers & Explorers
THE CONSUMER
SPECIFIC
USER
TYPES:
Needs to be
informed and/or
enabled in an
easily digested
manner
THE EXPLORER
Needs to be
provided with:
• an exploratory
capability
• a versatile set of tools
• a versatile set of
visualizations
• training/education
46. Two Distinct Modes
There are two distinct modes of information usage:
u REAL-TIME/BUSINESS-TIME:
Information is a
contributor to another activity
u CONTEMPLATIVE
•
•
•
ANALYSIS:
Information is a material to work with and
analyze
Visualization contributes to this analysis
Just as there are statistical algorithms, there
are visual algorithms
NOTE THAT ANIMATION ADDS A DIMENSION.
WE CAN SEE THINGS VIA ANIMATION THAT WOULD
OTHERWISE BE INVISIBLE.
48. u What
does IBM know about the effectiveness of
any specific visualization and how do we know it?
How is it measured?
u Is
there a relationship between visualization and
data volumes? If so, what is it?
u Are
some people poor at deriving meaning from
visualization – and yet skilled in other ways?
u What
is the learning dimension and how is it
characterized?
49. u What
does IBM know about animation and
cognition, if anything?
u You
suggest that there are best practices. How
do we know – what research has been done? Are
there cultural variances?
u Are
there visualizations that are yet to be
discovered?