claw 2017 tableau slides (buhler, magnus) (read-only) · outline •...
TRANSCRIPT
Purposeful Data Visualization with Tableau
Jeremy Buhler, Assessment Librarian, UBC | [email protected]
Ebony Magnus, Assessment & User Experience Librarian, SAIT | [email protected]
Workshop material and data files athttp://bit.ly/claw-‐tableau
Please download copy of Excel files
Outline
• what we mean by “purposeful”• preparing your data• introducing the Tableau interface• exercise/practice
break, 10:30-‐11:00
• creating dashboards• exercise/practice• refining the visual presentation• exercise/practice
Goals
• not intimidated by the software• curious about what more it can do• prepared to tackle your own datasets
data visualization
“all types of visual representation that support the exploration, examination, and
communication of data” (Few, 2009)
objects
pointslinesbars
relationships
time-‐seriesnominal comparisonrankingpart-‐to-‐wholedeviationcorrelationgeospatial
pre-‐attentive processing
the perception of basic attributes “prior to and without the need for conscious awareness” (Few, 2009)
Attentive processing
Preattentive processing
From Stephen Few, Tapping the Power of Visual Perceptionhttp://www.perceptualedge.com/articles/ie/visual_perception.pdf
form
length width orientation
shape
size
blurcurvature enclosure
colour position motion
hue
intensity
2-‐D position direction of motion
spatial grouping
data cleaning & prep
more polished =more true?
more polished =more true?
faster = better?
more polished =more true?
faster = better?
understand your data, understand your tools
Choosing and preparing your data
• level of detail or aggregation• format• privacy• description• quality
Choosing and preparing your data
• choose raw over aggregated data• normalize cross-‐tabulated datasets
Choosing and preparing your data
• choose raw over aggregated data• normalize cross-‐tabulated datasets
Related resource: Preparing Excel files for analysis [in Tableau]. http://kb.tableau.com/articles/knowledgebase/preparing-‐excel-‐files-‐analysis
Tall data, not wide
raw vs aggregated data
raw vs aggregated data
tall vs cross-‐tabulated (wide) data
tall vs cross-‐tabulated (wide) data
tall vs cross-‐tabulated (wide) data
Like with like, in the same column
<software demo and hands-‐on practice>
Junk drawer, tickle trunkTry to break your viz. Throw everything at it, try things you don’t understand, create a mess and see what you find.
<software demo and hands-‐on practice>
Participants encouraged to share examples athttps://public.tableau.com/profile/claw.2017
Explore your chosen data set. Try to identify one pattern, one outlier, and one relationship. Consider how this changes your initial assumptions about the service or product represented in the data set.
<software demo and hands-‐on practice>
Communicate something of import about your data set. Consider who you’re speaking to and what you hope to accomplish. Use Tableau’s features strategically to highlight aspects of your data that are most important to your message.
<hands-‐on practice>