D ATA V I S U A L I Z AT I O N
I N P R O D U C T
P R O D U C T C A M P B O S T O N 2 0 1 6
C T O D D L O M B A R D O
C H I E F D E S I G N S T R A T E G I S T - F R E S H T I L L E D S O I L
@ I A M C T O D D
S O U R C E : H T T P : / / S Q L - J O I N S . L E O PA R D . I N . U A /
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W H AT A B O U T M O B I L E ?
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S O U R C E : B R I G H T P O I N T I N C . C O M
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W H E R E D O Y O U S TA R T ?
H O W - T O
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D ATA C O N S U M E R
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D ATA E N C O D E C O N S U M E R
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D ATA E N C O D E C O N S U M E R
V I S U A L I Z AT I O N
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D ATA E N C O D E D E C O D E C O N S U M E R
V I S U A L I Z AT I O N
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T H E R E A R E M A N Y A P P R O A C H E S …
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T H E R E A R E M A N Y A P P R O A C H E S …
A C Q U I R E PA R S E F I LT E R M I N E R E P R E S E N T R E F I N E I N T E R A C T
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T H E R E A R E M A N Y A P P R O A C H E S …
A C Q U I R E PA R S E F I LT E R M I N E R E P R E S E N T R E F I N E I N T E R A C T
C L A R I F Y W H AT & W H Y E X P L O R E & S K E T C H D E F I N E & P R O D U C E M A I N TA I N & A N A LY Z E
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T H E R E A R E M A N Y A P P R O A C H E S …
A C Q U I R E PA R S E F I LT E R M I N E R E P R E S E N T R E F I N E I N T E R A C T
C L A R I F Y W H AT & W H Y E X P L O R E & S K E T C H D E F I N E & P R O D U C E M A I N TA I N & A N A LY Z E
A C Q U I R E C L E A N I N T E G R AT E V I S U A L I Z E M O D E L P R E S E N T D I S S E M I N AT E
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T H E R E A R E M A N Y A P P R O A C H E S …
A C Q U I R E PA R S E F I LT E R M I N E R E P R E S E N T R E F I N E I N T E R A C T
C L A R I F Y W H AT & W H Y E X P L O R E & S K E T C H D E F I N E & P R O D U C E M A I N TA I N & A N A LY Z E
A C Q U I R E C L E A N I N T E G R AT E V I S U A L I Z E M O D E L P R E S E N T D I S S E M I N AT E
E S TA B L I S H
C O N T E X T
A C Q U I R E &
P R E PA R E D ATA
E D I T O R I A L
F O C U S
D E S I G N
C O N S T R U C T &
E VA L U AT E
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T H E R E A R E M A N Y A P P R O A C H E S …
A C Q U I R E PA R S E F I LT E R M I N E R E P R E S E N T R E F I N E I N T E R A C T
C L A R I F Y W H AT & W H Y E X P L O R E & S K E T C H D E F I N E & P R O D U C E M A I N TA I N & A N A LY Z E
A C Q U I R E C L E A N I N T E G R AT E V I S U A L I Z E M O D E L P R E S E N T D I S S E M I N AT E
E S TA B L I S H
C O N T E X T
A C Q U I R E &
P R E PA R E D ATA
E D I T O R I A L
F O C U S
D E S I G N
C O N S T R U C T &
E VA L U AT E
K N O W T H E
A U D I E N C E
K N O W T H E
D ATA
U N D E R S TA N D
C O N T E X T
C O M M U N I C AT E
S I M P LY
C O M M U N I C AT E
C L E A R LY
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K N O W T H E
A U D I E N C E
K N O W T H E
D ATA
U N D E R S TA N D
C O N T E X T
C O M M U N I C AT E
S I M P LY
C O M M U N I C AT E
C L E A R LY
P R O D U C T V I S U A L I Z AT I O N D E S I G N A P P R O A C H
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V I S U A L I Z AT I O N D E S I G N P R I N C I P L E S
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V I S U A L I Z AT I O N D E S I G N P R I N C I P L E S
• Elegant
• Truthful
• Accessible
• Justified
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1. Know the audience
2. Know the data
3. Know the story
4. Communicate simply
5. Communicate clearly
V I S U A L I Z AT I O N D E S I G N P R I N C I P L E S
• Elegant
• Truthful
• Accessible
• Justified
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1 . K N O W T H E A U D I E N C E
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1 . K N O W T H E A U D I E N C E
• What questions do they have?
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1 . K N O W T H E A U D I E N C E
• What questions do they have?
• How will they use this information to make decisions?
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1 . K N O W T H E A U D I E N C E
• What questions do they have?
• How will they use this information to make decisions?
• What level of familiarity do they have with the source data?
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1 . K N O W T H E A U D I E N C E
• What questions do they have?
• How will they use this information to make decisions?
• What level of familiarity do they have with the source data?
• How often will they be using this information?
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1 . K N O W T H E A U D I E N C E
• What questions do they have?
• How will they use this information to make decisions?
• What level of familiarity do they have with the source data?
• How often will they be using this information?
• What level of sophistication do they with analytics/statistics?
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1 . K N O W T H E A U D I E N C E
• What questions do they have?
• How will they use this information to make decisions?
• What level of familiarity do they have with the source data?
• How often will they be using this information?
• What level of sophistication do they with analytics/statistics?
• Is your visualization more exploratory or explanatory?
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A U D I E N C E A S K S
Q U E S T I O N ,
S E E S D ATA ,
G E T S A N S W E R
A U D I E N C E S E E S D ATA ,
A S K Q U E S T I O N S ,
E X P L O R E S D ATA ,
G E T S A N S W E R
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2 . K N O W T H E D ATA
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
• What questions can the data answer?
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
• What questions can the data answer?
• How old/new is the data?
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
• What questions can the data answer?
• How old/new is the data?
• What are the inherent relationships between values?
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
• What questions can the data answer?
• How old/new is the data?
• What are the inherent relationships between values?
• What other data can we combine with it?
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
• What questions can the data answer?
• How old/new is the data?
• What are the inherent relationships between values?
• What other data can we combine with it?
• What assumptions will you have to make?
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2 . K N O W T H E D ATA
• What is the quality of the data? Can you trust it?
• What questions can the data answer?
• How old/new is the data?
• What are the inherent relationships between values?
• What other data can we combine with it?
• What assumptions will you have to make?
• Does a data dictionary exist?
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C O R R E L AT I O N ≠ C A U S AT I O N
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H T T P : / / W W W. T Y L E R V I G E N . C O M / S P U R I O U S - C O R R E L AT I O N S
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3 . U N D E R S TA N D T H E C O N T E X T
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3 . U N D E R S TA N D T H E C O N T E X T
• What does the data tell you?
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3 . U N D E R S TA N D T H E C O N T E X T
• What does the data tell you?
• How is the data insightful or interesting to your user?
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3 . U N D E R S TA N D T H E C O N T E X T
• What does the data tell you?
• How is the data insightful or interesting to your user?
• Why is your finding occurring or not occurring?
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3 . U N D E R S TA N D T H E C O N T E X T
• What does the data tell you?
• How is the data insightful or interesting to your user?
• Why is your finding occurring or not occurring?
• How will this help your users?
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3 . U N D E R S TA N D T H E C O N T E X T
• What does the data tell you?
• How is the data insightful or interesting to your user?
• Why is your finding occurring or not occurring?
• How will this help your users?
• What decisions will they need to make?
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3 . U N D E R S TA N D T H E C O N T E X T
• What does the data tell you?
• How is the data insightful or interesting to your user?
• Why is your finding occurring or not occurring?
• How will this help your users?
• What decisions will they need to make?
• What are their next steps?
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Things that make you go “Hmmm…”
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4 . C O M M U N I C AT E S I M P LY
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4 . C O M M U N I C AT E S I M P LY
• How long does it take for your audience to arrive at your conclusion?
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4 . C O M M U N I C AT E S I M P LY
• How long does it take for your audience to arrive at your conclusion?
• Is the message delivered accurately & consistently?
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4 . C O M M U N I C AT E S I M P LY
• How long does it take for your audience to arrive at your conclusion?
• Is the message delivered accurately & consistently?
• [Interactive] How many clicks to find the answer to their question?
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4 . C O M M U N I C AT E S I M P LY
• How long does it take for your audience to arrive at your conclusion?
• Is the message delivered accurately & consistently?
• [Interactive] How many clicks to find the answer to their question?
• Where do they go in your app next?
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O H D E A R . .
B E C A U S E Y O U C A N . . S H O U L D Y O U ?
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5 . C O M M U N I C AT E C L E A R LY
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5 . C O M M U N I C AT E C L E A R LY
• What are the key findings & messages?
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5 . C O M M U N I C AT E C L E A R LY
• What are the key findings & messages?
• What is the right way to visualize the findings?
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5 . C O M M U N I C AT E C L E A R LY
• What are the key findings & messages?
• What is the right way to visualize the findings?
• How do they interpret the data?
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5 . C O M M U N I C AT E C L E A R LY
• What are the key findings & messages?
• What is the right way to visualize the findings?
• How do they interpret the data?
• What decisions will they make from this visualization?
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5 . C O M M U N I C AT E C L E A R LY
• What are the key findings & messages?
• What is the right way to visualize the findings?
• How do they interpret the data?
• What decisions will they make from this visualization?
• Is it easy to understand the findings?
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A D A M M C C A N N , TA B L E A U Z E N M A S T E R
If the meaning of the data is not conveyed,
the visualization is a failure.
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D ATA : I N K R AT I O
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S O U R C E : B R I G H T P O I N T I N C . C O M
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D A S H B O A R D S
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— S H N E I D E R M A N
“Overview First, Zoom and Filter,
Then Details-on-Demand”
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T H E S E V E N TA S K S O F I N F O V I Z U S E R S
• Overview: Gain an overview of the entire collection.
• Zoom : Zoom in on items of interest
• Filter: Filter out uninteresting items.
• Details-on-demand: Select an item or group and get details when needed
• Relate: View relationships among items.
• History: Keep a history of actions to support undo, replay, and query parameters.
• Extract: Allow extraction of sub-collections and of the progressive refinement.