takingbigdata
visually
March 4, 2014

2014 Analytics with Purpose
Behavioral Insight to Advantage
San Diego, California

C...
 challenges in data volume
and velocity

what we’ll look at

 how we’re wired for sight
 creating visual stories

© 201...
THE REALITY

we’re generating
a LOT of data

© 2014 SapientNitro
%
of the data in the world today was created in
the last 2 years alone.
- IBM -

© 2014 SapientNitro
This is the volume of photos
uploaded to Flikr in a single day

© 2014 SapientNitro
THE PROBLEM

we’re generating
too much, too fast

© 2014 SapientNitro
we’re accumulating data faster
than our ability to understand it

ibm
© 2014 SapientNitro
a new
wave of
data is on
the horizon
innovations in wearables
and biometrics will drive a
surge in physiological data
© 20...
190,000
people with deep analytic sills as well as

1.5 million
managers and analysts will be needed by
2018 to fill jobs ...
THE OTHER PROBLEM

we don’t think in
numbers

© 2014 SapientNitro
an egg
This is your brain,

a pan
this is your brain,

a shift
this is your brain on drugs,

Any questions?

this famous p...
our brains process visual information

,

times faster than text

© 2014 SapientNitro
%

%

of our brains are involved in

of all of our

visual processing

sensory receptors
are in our eyes

© 2014 SapientNi...
THE SOLUTION

visualization

© 2014 SapientNitro
FOR PEOPLE

visualization

helps make data clearer and more engaging

© 2014 SapientNitro
FOR BUSINESS

visualization

helps make data actionable and easier to manage

© 2014 SapientNitro
visualization
is about asking

an intriguing question
© 2014 SapientNitro
visualization
is answered with

contextual data
© 2014 SapientNitro
visualization
is expressed in

an engaging way
© 2014 SapientNitro
visualizations
are created from one of two perspectives
rational




literal
quantifiable
pragmatic

creative




me...
visual storyscapes
are created when you combine the two
insightful
revealing
engaging

© 2014 SapientNitro
“Stories are just
data with a soul”
Dr. BreneBrown
Research Storyteller
University of Houston

© 2014 SapientNitro
what’s an intriguing
question?

© 2014 SapientNitro
BAD QUESTION

do these
jeans make
me look fat?
© 2014 SapientNitro
TRICK QUESTION

do you know
why I stopped
you?
© 2014 SapientNitro
INTRIGUING QUESTION

how is the
moon like an
Oreo cookie?
© 2014 SapientNitro
where do you find
contextual data?

© 2014 SapientNitro
what you’re
doing

who you are

what you’ve
done

who you
do it with

retail
© 2014 SapientNitro
what ‘s your
lifestyle?

why are
you here?

how much do
you need?

how much
you deposit

how much
you withdraw

banking
© ...
what
changed?

what was?

why did it
change?

what did the
change
change?

change
© 2014 SapientNitro
how can data
stories engage?

© 2014 SapientNitro
four types of

visual
engagement

1. collective
2. descriptive
3. adaptive
4. predictive

© 2014 SapientNitro
collective

visualizations summarize data

modern history

payment patents

how search works

deltasight.com

interactive ...
descriptive

visualizations share data-driven snapshots

consumer intelligence
the consumer barometer

relative time

reta...
adaptive

visualizations adapt to real time data feeds

social mapping

fitness monitoring

spatial awareness

google maps...
predictive

visualizations offer the ability to
future-cast and explore conditional scenarios

career advisor

life coach
...
story complexity

complexity of
the data will
point to the
best option for
visualization

type of visualization
© 2014 Sap...
following a single
strand of hair
A VISUAL STORYSCAPE

© 2014 SapientNitro
In a world full of mobile savvy shoppers and
aisles bursting with hair care products,

how can one box of
hair color rule ...
data considerations
84% of guests use their smartphone while in a
store…but what are they actually doing?
Is ‘showrooming’...
 Smartphone use and
behavior tracking
 Location-based, interactive
phone questionnaire

data dive
deploy device activity...
learning
environment
 passive infrared sensors and
sound collectors
 heat sensors collect data on
paths, dwell times, en...
smartphone





Unobtrusive widget runs in OS background
Logs what people do on their phones 24/7
Data pushed to data w...
contextual continuity
© 2014 SapientNitro
snackable moments

© 2014 SapientNitro
THE CAVEAT

believing what we
see isn’t always a
good thing

© 2014 SapientNitro
this visualization overemphasizes the impact of non-communicable diseases

This graphic lumps together pneumonia deaths at...
visualization is a collaborative sport
strategist

designer

developer

what are the primary
and supporting data
points to...
 ask an intriguing question
 gather the right contextual
data

visualize
this!

 make sure your data is clean,
accurate...
a parting visualization

the life you have in jelly beans
© 2014 SapientNitro
thank you
takingbigdata
visually
March 4, 2014

Charles Sayers
Experience Innovation
SapientNitro
csayers@sapient.com
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Taking Big Data Visually

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This is a presentation I made to the AMA Data with Purpose conference in March 2014. I looks at the current surge in data and how to create and share data stories to help make data more understandable and actionable.

Published in: Technology

Taking Big Data Visually

  1. 1. takingbigdata visually March 4, 2014 2014 Analytics with Purpose Behavioral Insight to Advantage San Diego, California Charles Sayers Experience Innovation SapientNitro csayers@sapient.com
  2. 2.  challenges in data volume and velocity what we’ll look at  how we’re wired for sight  creating visual stories © 2014 SapientNitro
  3. 3. THE REALITY we’re generating a LOT of data © 2014 SapientNitro
  4. 4. % of the data in the world today was created in the last 2 years alone. - IBM - © 2014 SapientNitro
  5. 5. This is the volume of photos uploaded to Flikr in a single day © 2014 SapientNitro
  6. 6. THE PROBLEM we’re generating too much, too fast © 2014 SapientNitro
  7. 7. we’re accumulating data faster than our ability to understand it ibm © 2014 SapientNitro
  8. 8. a new wave of data is on the horizon innovations in wearables and biometrics will drive a surge in physiological data © 2014 SapientNitro
  9. 9. 190,000 people with deep analytic sills as well as 1.5 million managers and analysts will be needed by 2018 to fill jobs in Big Data © 2014 SapientNitro
  10. 10. THE OTHER PROBLEM we don’t think in numbers © 2014 SapientNitro
  11. 11. an egg This is your brain, a pan this is your brain, a shift this is your brain on drugs, Any questions? this famous public service campaign signaled a shift in data story telling from numbers and statistics to emotional metaphor © 2014 SapientNitro
  12. 12. our brains process visual information , times faster than text © 2014 SapientNitro
  13. 13. % % of our brains are involved in of all of our visual processing sensory receptors are in our eyes © 2014 SapientNitro
  14. 14. THE SOLUTION visualization © 2014 SapientNitro
  15. 15. FOR PEOPLE visualization helps make data clearer and more engaging © 2014 SapientNitro
  16. 16. FOR BUSINESS visualization helps make data actionable and easier to manage © 2014 SapientNitro
  17. 17. visualization is about asking an intriguing question © 2014 SapientNitro
  18. 18. visualization is answered with contextual data © 2014 SapientNitro
  19. 19. visualization is expressed in an engaging way © 2014 SapientNitro
  20. 20. visualizations are created from one of two perspectives rational    literal quantifiable pragmatic creative    metaphorical relatable emotional © 2014 SapientNitro
  21. 21. visual storyscapes are created when you combine the two insightful revealing engaging © 2014 SapientNitro
  22. 22. “Stories are just data with a soul” Dr. BreneBrown Research Storyteller University of Houston © 2014 SapientNitro
  23. 23. what’s an intriguing question? © 2014 SapientNitro
  24. 24. BAD QUESTION do these jeans make me look fat? © 2014 SapientNitro
  25. 25. TRICK QUESTION do you know why I stopped you? © 2014 SapientNitro
  26. 26. INTRIGUING QUESTION how is the moon like an Oreo cookie? © 2014 SapientNitro
  27. 27. where do you find contextual data? © 2014 SapientNitro
  28. 28. what you’re doing who you are what you’ve done who you do it with retail © 2014 SapientNitro
  29. 29. what ‘s your lifestyle? why are you here? how much do you need? how much you deposit how much you withdraw banking © 2014 SapientNitro
  30. 30. what changed? what was? why did it change? what did the change change? change © 2014 SapientNitro
  31. 31. how can data stories engage? © 2014 SapientNitro
  32. 32. four types of visual engagement 1. collective 2. descriptive 3. adaptive 4. predictive © 2014 SapientNitro
  33. 33. collective visualizations summarize data modern history payment patents how search works deltasight.com interactive timeline the rei 1440 project © 2014 SapientNitro
  34. 34. descriptive visualizations share data-driven snapshots consumer intelligence the consumer barometer relative time retail dwell time here is today how retailers track you when you shop © 2014 SapientNitro
  35. 35. adaptive visualizations adapt to real time data feeds social mapping fitness monitoring spatial awareness google maps tictrac british airways © 2014 SapientNitro
  36. 36. predictive visualizations offer the ability to future-cast and explore conditional scenarios career advisor life coach the existential calculator Reporter app for iPhone financial manager MoneyWiz personal finance © 2014 SapientNitro
  37. 37. story complexity complexity of the data will point to the best option for visualization type of visualization © 2014 SapientNitro
  38. 38. following a single strand of hair A VISUAL STORYSCAPE © 2014 SapientNitro
  39. 39. In a world full of mobile savvy shoppers and aisles bursting with hair care products, how can one box of hair color rule them all? © 2014 SapientNitro
  40. 40. data considerations 84% of guests use their smartphone while in a store…but what are they actually doing? Is ‘showrooming’ something to worry about? © 2014 SapientNitro
  41. 41.  Smartphone use and behavior tracking  Location-based, interactive phone questionnaire data dive deploy device activity loggers onto the smartphones of a community of Shoppers to obtain detailed data on use both in-store and out of store © 2014 SapientNitro
  42. 42. learning environment  passive infrared sensors and sound collectors  heat sensors collect data on paths, dwell times, entry and exit points, fixture interactions  sound data is collected as a means to understand human interactions
  43. 43. smartphone    Unobtrusive widget runs in OS background Logs what people do on their phones 24/7 Data pushed to data warehouse for analysis questionnaire  Helps us understand context and drivers of a trip; ultimately match trip types of to phone behavior and use
  44. 44. contextual continuity
  45. 45. © 2014 SapientNitro
  46. 46. snackable moments © 2014 SapientNitro
  47. 47. THE CAVEAT believing what we see isn’t always a good thing © 2014 SapientNitro
  48. 48. this visualization overemphasizes the impact of non-communicable diseases This graphic lumps together pneumonia deaths at age 1 with car accidents at age 20, and cancer deaths at 50 with heart disease deaths at 80. http://www.informationisbeautiful.net/visualizations/20th-century-death/ © 2014 SapientNitro
  49. 49. visualization is a collaborative sport strategist designer developer what are the primary and supporting data points to our story? how do we convey that story visually? how do we enable our story? © 2014 SapientNitro
  50. 50.  ask an intriguing question  gather the right contextual data visualize this!  make sure your data is clean, accurate and complete  choose the best type of visual engagement  visualize truthfully  collaborate from start to finish © 2014 SapientNitro
  51. 51. a parting visualization the life you have in jelly beans © 2014 SapientNitro
  52. 52. thank you takingbigdata visually March 4, 2014 Charles Sayers Experience Innovation SapientNitro csayers@sapient.com

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