the zen of visual analysis

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The Zen of Visual Analysis

Chris StolteVice President, Engineering & co-founder

Jock MackinlayDirector, Visual Analysis


How do people reason about data?


The Cycle of Visual Analysis


“Wildlife Strike Database”http://wildlife-mitigation.tc.faa.gov/public_html/index.html


Not just

“Aha!”


advice:

Iterate, explore, and

experiment …regardless of task


How do we empower individuals and groups to

effectively analyze and share data?


Support the“Cycle of Visual Analysis”


IncrementalExpressiveUnifiedDirect


Supporting the “Cycle of Visual Analysis”: Incremental

Allow people to easily and incrementally change the data and how they are looking at it

click click


advice:

Start simple…


There is no single view for all tasks and all data

Supporting the “Cycle of Visual Analysis”:

Expressive



Expressive


advice:Reverse your thinking

– start with the data


versus

Traditional Reporting Tools

Traditional Visualization Tools

Tableau


Unification with the database


Leverage the revolutionary changes

in database technology


Unification with the database


Make the tool disappear. Allow the user to directly interact with the data.


Direct Interaction


How is this possible?

VizQL


Generate Effective Views of Data


People should not have to be

graphic designers or psychologists.


An effective presentation of data:• Communicates all of the data• Communicates only the data• Leverages the human perceptual system• Is understandable• Is interpretable

Generating Effective Views of Data


Communicates all of relevant data

Bad Bad Good



Bad

Communicates only the data

Bad



Bad Good

Leverages thehuman perceptual system



Isunderstandable



advice:Keep your visuals simple


Isinterpretab

le



advice:Annotate but remain focused


How does Tableau support generating effective views of data?

– Best practices are built into the product• Great defaults• Show Me and Show Me Alternatives• Small multiples

– Limiting the visual properties to a proven set– Titling, captioning, and annotation



Generate Beautiful Results


Share Interactive Views


Communicate all the data Demonstrate your confidenceAllow people to test your conclusionsLet your audience engage directly with the data



advice:Empower your audience –share interactive views


Aggregated Underlying



advice:Data is a dishbest served raw



Ad hoc analysis often reveals effective patterns of analysis.


advice:Leave a trail – model effective analysis with actions.


How do I design for interaction?



“Overview first, zoom & filter,

then details-on-demand.”

Ben Shneiderman’s mantra:


Quick filtersFiltering actionsView underlying dataTooltipsMaster-detail


Jacques Bertin’s permutation matrices:Share Interactive Views

Programmatic sort1-click sort


advice:know your audience and design for their questions



Task: Finding an object and viewing it “in context”

Wildcard filterText listsHighlighting



Task: Finding and understanding relationships

Dashboards with multiple perspectivesHighlighting



Interaction “resiliency”:Think about how your views will change when people interact


“Wildlife Strike Database”http://wildlife-mitigation.tc.faa.gov/public_html/index.html


Who can Visual Analysis help?

Anybody with data and questions


advice:Do not limit yourself tolarge data or special projects


advice:Seekoutside inspiration


SummaryIterate, explore, and experiment regardless of taskStart simpleReverse your thinking and start with the dataKeep your visuals simpleAnnotate but remain focusedUse small multiplesEmpower your audience by sharing interactive viewsData is a dish best served rawLeave a trail – model effective analysis with actionsKnow your audience and design for their questionsDon’t limit yourself to large dataSeek outside inspiration

the zen of visual analysis

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