what is data visualization
practise of representing data visually
tto transform info with the influence of purposeful design and analytics with the intent of encoding and conveying info otherwise difficult to understand in a meaningful way
what are emphasis guidelines for dashboards
most emphasis to least emphasis:
top right to bottom left
what are the categories of data vis.
exploratory, hybrid, explanatory
exploratory:
- highest bar on histogram, peak on line chart
what are the 4 use cases for data visualization
to record, analyze and reveal, confirm, and communicate
what are duell’s rules for actionable visualizations
The question to answer must be identifiable*
Articulate the question you wish to answer and write it out:
“I want to know who my best customers are.”
“ I need to be able to identify customers at risk.”
“How is our sales team performing against its goals?”
*Note – This is different from Exploratory Data Analysis
what are dashboard do’s
Content position and size should match its importance and frequency of use
Use color and formatting to draw attention where needed, rather than to decorate
Visually associate data and content that is related
Use the needs of the user to drive the layout, rather than forcing layout with an
inflexible grid
(note: this is a consideration when choosing tools)
When deciding placement,
consider how the eye will scan the
page…
what are shaffer 4 c’s of data visualization
Clear - easily seen; sharply defined
* who’s the audience? what’s the message?
* clarity more important than aesthetics
Clean - thorough; complete
* labels, axis, gridlines, formatting, right chart type, color choice, etc.
Concise - brief but comprehensive
* not minimalist but not verbose
Captivating - to attract and hold by beauty or excellence
* does it capture attention? is it interesting? does it tell the story?
what is the storytelling with data process
- understand content
- who is audience, what do you need them to do, how will data help make your point
- articulate big idea
- create storyboard - choose an appropriate visual
- draw it, then create it in your tool
- iterate and look at your data different ways
- seek feedback - eliminate clutter
- identify unnecessary elements and remove them
- leverage white space, align elements, avoid diagonal components
- aim for clean horizontal and vertical components, avoid diagonals - draw attention where you want it
- use position, size and colour to focus attention
- “what do you see first” - think like a designer
- first function: think abt what you want your audience to do with the data (analyze fine detail, comm, key trends)
- second form: create visualization that will make this easy
– affordances: aspects of design that make it obvious how to use (highlight important stuff and eliminate distractions)
– accessibility: design that is usable by people of widely varying technical skills (make it legible, clean, plain language, no unnecessary complexity)
– aesthetics: more visually appealing designs are perceived as easier to use and are more readily accepted (smart with colour, alignment, leverage white space)
– acceptance: for design to be effective, it must be accepted by the intended audience (articulate benefits, side by side, provide multiple options/seek input, vocal audience member on board) - tell a story
- return to storyboard
- use narrative arc ot plan story and form a pithy, repeatable phrase to help message stick
what is the gestalt principle
Proximity: when things are close together, they appear to be more related.
Similarity: when things appear to be similar to each other, they will automatically be grouped together.
Enclosure: we perceive objects enclosed as groups.
Closure: When we view a shape, we prefer when it is complete.
Continuity: if an element is arranged on a curve or a line, it is perceived to be more related than other elements not on the line or the curve.
Connection: connected are perceived more related.
what are tufte’s 5 laws of data ink
- Above all else show the data.
- Maximize the data-ink ratio
- Erase non-data-ink.
- Erase redundant data-ink.
- Revise and edit.
