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Your data should be comprehensive and from a reliable source, and you want to make sure you're working with the right amount of data. Provide too little data and your chart won’t be convincing. Too much, and your chart could get confusing.
Four steps before starting data visualization
- Identify your audience.
- Decide on your story.
- Double-check your data
- Choose the right amount of data
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The third step to take before
starting a visualization is to
0:00
double-check your data.
0:04
I've included an article from HubSpot
in the teacher's notes called How to
0:06
Find Accurate and Compelling Data.
0:11
HubSpot notes that your data must
be tracked to its original source.
0:14
If you or your colleagues didn't
personally gather this data,
0:19
work to find the original source.
0:22
What methods were used
in obtaining the data?
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How large was the sample size?
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Your data should be comprehensive.
0:30
If you're gathering sales numbers
from April and May of last year,
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check out the surrounding months to
view those numbers in a larger context.
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And your data should be
as current as possible.
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If you're forced to use older data,
make it obvious within your presentation.
0:46
You also want to make sure
the source of your data is reliable.
0:52
HubSpot provides a checklist for
judging the reliability of online data.
0:57
Including checking the credentials
of the author and organization,
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how recently the website was updated,
and the purpose of the organization.
1:07
HubSpot also includes links to
a number of reliable sources of data.
1:12
So this might be a good page to bookmark
the next time you're double checking data.
1:17
Finally, make sure you're working
with the right amount of data.
1:24
Provide too little data and your chart
won't be convincing, too much and
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your chart could get confusing.
1:32
I'm looking at a site called
Basketball Reference,
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which contains the largest collection
of basketball stats I've ever seen.
1:38
When looking over Dennis Rodman's career,
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you might be tempted to include
his height in your chart.
1:45
It certainly is impressive that at
6 foot 7 Rodman was able to take
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rebounds away from taller players.
1:53
But does that contribute to the
story that Rodman was the most
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efficient rebounder of all time?
1:59
Not really.
2:02
We can similarly throw away any stats
related to shooting, passing, or
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playoff performance.
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Anything not directly related to
rebounding would clutter our chart.
2:10
Even when we focus on rebounding,
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we only want what will help us
compare players across eras,
2:17
such as rebounds per 100 possessions and
total rebound percentage.
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When deciding what data to include,
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be sure to consider where
this data will be seen.
2:31
Are you making charts for
a blog like Skeptical Sports?
2:34
If so, you'll have a little more space
to introduce some of your more advanced
2:39
concepts and explain how
your calculations were made.
2:43
Some charts such as the Wall Street
Journal job market tracker
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are interactive,
allowing users to
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see how data changes when
different variables are introduced.
2:53
However, if your chart is being printed,
or if it's meant to be shared on social
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media by itself, you'll need to make sure
the chart can be understood on its own,
3:03
independent of any supporting
article or interactivity.
3:08
Once you've identified your audience,
decided on your story,
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double-checked your data, and chosen
the right amount of data to include,
3:17
it's time to select the right visual for
conveying your information.
3:22
We'll start looking at different
types of charts in our next stage.
3:26
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