This document contains summaries and excerpts from the Harvard Business Review article "When Data Visualization Works — And When It Doesn’t" published on March 27, 2013. It discusses three reasons for visualizing data: confirmation, education, and exploration. It also addresses factors that influence the effectiveness of data visualization like data quality, context, and creator biases.

1. 주간 데이터.읽어주는.남자
2번째 순서

2. 김영웅
주간 데이터 읽어주는 남자
꿈꾸는 데이터 디자이너 매니저
경영정보시스템 전공 박사과정
경영전문대학원 MBA
컴퓨터공학 전공
Ryan Kim | Convergence Business Designer
Facebook. https://www.facebook.com/keyassist
E-mail. youngwung.kim@gmail.com
Web. http://keyassist.tistory.com

3. When Data Visualization Works
— And When It Doesn’t

4. data visualization is about
communicating
an idea that will drive action.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

5. the reasoning behind constructing
data visualizations will help you do
that with efficiency and impact.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

6. For information to provide
valuable insights,
it must be
interpretable, relevant, and novel.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

7. Collecting lots of data without
the associated metadata
reduces the opportunity
to play with, interpret, and gain
insights from the data.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

8. It must also be relevant to the persons
who are looking to gain insights,
and to the purpose for which
the information is being examined.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

9. it must be original, or shed new light
on an area. If the information fails
any one of these criteria, then no
visualization can make it valuable.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

10. There are three broad reasons
for visualizing data
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

11. Confirmation:
If we already have a set of assumptions
about how the system we are interested in.
visualizations can help us
check those assumptions.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

12. Education:
One is simply reporting.
The other is to develop
intuition and new insight.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

13. Exploration:
We can use visualization to help
build a model to allow us to predict
and better manage the system.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

14. what gives us confidence
that these insights are
now worthy of action?
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

15. Data quality: The quality of the underlying
data is crucial to the value of visualization.
How complete and reliable is it?
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

16. Context: The point of visualization is to
make large amounts of data approachable
so we can apply our evolutionarily honed
pattern detection computer
to draw insights from it.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

17. To leave out any contextual information
or metadata (or more appropriately,
“metacontent”) is to risk hampering
our understanding.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

18. Biases: The creator of the visualization
may influence the semantics of the
visualization. any of which can challenge
the interpretation of the data.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

19. This also creates the risk of “pre-specifying”
discoverable features and results via the
embedded algorithms used by the creator.
Harvard Business Review MARCH 27, 2013 “When Data Visualization Works — And When It Doesn’t”

20. When Data Visualization Works
— And When It Doesn’t

21. The Best Data Visualization
Projects of 2014
<source=http://flowingdata.com/>

22. The Upshot

23. Where We Came From and Where We Went

24. The Most Detailed Maps You’ll See
From the Midterm Elections

25. How the Recession Reshaped
the Economy, in 255 Charts

26. Visualizing Algorithms
Mike Bostock

27. Bostock demonstrated processes and patterns in a wide array
of algorithms for sorting, sampling, and maze generation.
The result was a useful learning resource and an appreciation for
something that's otherwise a challenge to imagine for most people.

28. Visualizing MBTA Data
An interactive exploration of Boston's subway system

29. Boston’s Massachusetts Bay Transit Authority (MBTA)
operates the 4th busiest subway system in the U.S.
after New York, Washington, and Chicago.

30. SELFIECITY
Investigating the style of self-portraits (selfies)
in five cities across the world

31. 주간 데이터.읽어주는.남자
2번째 순서

32. NeuroAssociates
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・ Phone : 02-334-2013