week 6

Question 1

what is data visualization

Answer 1

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

Question 2

what are emphasis guidelines for dashboards

Answer 2

most emphasis to least emphasis:
top right to bottom left

Question 2

what are the categories of data vis.

Answer 2

exploratory, hybrid, explanatory

exploratory:
- highest bar on histogram, peak on line chart

Question 3

what are the 4 use cases for data visualization

Answer 3

to record, analyze and reveal, confirm, and communicate

Question 4

what are duell’s rules for actionable visualizations

Answer 4

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

Question 4

what are dashboard do’s

Answer 4

 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…

Question 4

what are shaffer 4 c’s of data visualization

Answer 4

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?

Question 5

what is the storytelling with data process

Answer 5

1. understand content
   - who is audience, what do you need them to do, how will data help make your point
   - articulate big idea
   - create storyboard
2. choose an appropriate visual
   - draw it, then create it in your tool
   - iterate and look at your data different ways
   - seek feedback
3. 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
4. draw attention where you want it
   - use position, size and colour to focus attention
   - “what do you see first”
5. 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)
6. tell a story
   - return to storyboard
   - use narrative arc ot plan story and form a pithy, repeatable phrase to help message stick

Question 5

what is the gestalt principle

Answer 5

 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.

Question 6

what are tufte’s 5 laws of data ink

Answer 6

1. Above all else show the data.
2. Maximize the data-ink ratio
3. Erase non-data-ink.
4. Erase redundant data-ink.
5. Revise and edit.