This document provides guidance on best practices for data visualization. It begins by defining different types of data visualizations like dashboards, reports, and data storytelling. It then discusses principles of human perception and visualization guidelines. The document outlines best practices for specific visual types like time series, categorical data, maps, and use of color. It emphasizes that effective visualization requires both art and science skills to tell clear and meaningful stories with data.

1. Choose the Right
Visual
Lorenzo Vercellati

2. Lorenzo Vercellati
• Power BI Solution Architect @SolidQ
• BI Reporting Microsoft certified
• PUG Milan Leader, SQL Saturday Speaker,
DIAD Instructor
• 20 years burnin’ down the Data road
• Medieval History Graduated, Homebrewer,
Football and Movie addicted
• @supergimi
• Linkedin.com/in/lorenzovercellati/

3. Disclaimer

4. Session Objectives & Agenda
• Identify the best practice to develop an
effective and efficient data visualization
• Who is a data storyteller?
• Types and Goals of a data visualization
• Visualization Guidelines
• Main visuals Best practices

5. Between Art and Science

6. Data Cathedral

7. The Pillars of the Earth
Power Query Data Model Visuals

8. Product not Sum
Power Query Data Model Visuals

9. Product not Sum
When a pillar collapses,
the whole report falters

10. Welcome to the Report Cemetery

11. Focus on
Visuals

12. Who is a Data Storyteller?

13. Between Art and Science

14. Looking for a
Power
Leonardo

15. Artistic Half Skills
• Comunication
• Innovatation
• Taste
Scientist Half Skill
Knowledge of
• Perception Rules
• Visualization Best Practices
Skills

16. “Hard Work never beats Talent
when Talent works hard”

17. UI != UX

18. Different Data Visualizations
Dashboards Reports Data Storytelling

19. Dashboards
A dashboard is a visual display
of
the most important information needed to achieve one or more objectives
that has been
consolidated on a single computer screen
so it can be
monitored at a glance

20. Reports
• Data Analysis
• Interactions
• Drills
• You can prepare the
pitch, but the user
plays the game

21. Data Storytelling
• You tell the story
• You define the
timeline
• You can use more tools
and tricks

22. Human Perception

23. The Visualization Wheel
Density
Multidimensionality
Originality
Novelty
Figuration
Functionality
Abstraction
Redundancy
Familiarity
Unidimensionality
Lightness
Decoration

24. The Visualization Wheel
Density
Multidimensionality
Originality
Novelty
Figuration
Functionality
Abstraction
Redundancy
Familiarity
Unidimensionality
Lightness
Decoration

25. “Is beauty sometimes useful? Certainly.
Is beauty always useful?
Certainly not.”
- Stephen Few, “Should data visualization be beautiful?”

26. The Visualization Wheel
Density
Multidimensionality
Originality
Novelty
Figuration
Functionality
Abstraction
Redundancy
Familiarity
Unidimensionality
Lightness
Decoration

27. The Visualization Wheel
Density
Multidimensionality
Originality
Novelty
Figuration
Functionality
Abstraction
Redundancy
Familiarity
Unidimensionality
Lightness
Decoration

28. Differences
Human brain works better on tone
differences then on shape difference
4 3 6 7 9 8 1 2 5 5 1 1 5 6 1 1 5 8 1 3 4
1 5 3 4 5 1 1 5 2 6 1 3 1 9 2 5 1 2 1 8 9
5 2 1 6 1 1 6 1 2 4 1 8 1 6 1 5 8 2 1 4 1
1 4 1 8 1 9 5 1 2 8 1 9 1 1 5 1 1 5 1 1 6
2 6 1 9 1 5 1 2 2 1 4 1 6 1 8 2 1 4 1 2 4
4 3 6 7 9 8 1 2 5 5 1 1 5 6 1 1 5 8 1 3 4
1 5 3 4 5 1 1 5 2 6 1 3 1 9 2 5 1 2 1 8 9
5 2 1 6 1 1 6 1 2 4 1 8 1 6 1 5 8 2 1 4 1
1 4 1 8 1 9 5 1 2 8 1 9 1 1 5 1 1 5 1 1 6
2 6 1 9 1 5 1 2 2 1 4 1 6 1 8 2 1 4 1 2 4

29. Cleveland -
McGill

30. Let’s Visual

31. The Wild Bunch
34 Default
Visuals
100+ Custom
Visuals

32. The Wild Bunch
https://www.sqlbi.com/ref/power-
bi-visuals-reference/

33. No more Pie Chart
Leave them to those
who can really get
something out of it!

34. Rainbow Chart
• No evaluable difference
• Too many colors to manage
• Needs labels
• Needs legend

35. “If you can eat it,
Don’t use it in Power BI”

36. Just a small slice
Use pie chart only to
put in evidence a
single part vs. Total

37. Pie vs Bar Demo

38. Time Series
Use lines

39. Time Series
Sometimes column chart
Column, No bar! Time is from left to right

40. Categorical Data
Column or bar chart

41. Stacked Charts
Use moderately
They are the right choice only when we
must display multiple instances of a whole
and its parts, with emphasis on the whole

42. Stacked Charts
Rember Cleveland – McGill!

43. 100% Stacked Charts

44. Stacked Charts

45. Stacked Charts

46. Waterfall

47. Waterfall Revisited

48. Combo Chart
Different series in
the same chart
could suggest
correlation: be
sure correlation is
real!

49. Splitted Combo Chart
Split them if you have space enough

50. Relationships Between Measures
Scatterplot

51. Don’t use size if you can

52. Don’t use size if you can
7
?
13

53. Bubble Size Demo

54. Don’t use size if you can
>

55. Maps: Which one? When? How?
Out of
the Box
Vs.
Custom

56. Map
• Categorize your data to help Bing
Service
• Use combination of Location field
and Longitude and Latitude with
drill down for good results

57. Shape Map
A shape map is a visual built to
show comparisons of regions on a
map by applying different colors to
each region.
Create your custom shape maps
using mapshaper.org o free tools
like QGis
You can also update manually your
TopoJSON

58. Shape Map

59. Shape Map Demo

60. Is There Anybody Out There?

61. Mapbox
• Requires access token
• Shows large number of points
• Multiple background layers,
including custom
• Cluster, Heatmap, Circles &
Choropleth
• Need to aggregate data manually

62. Synoptic Panel

63. Tables and Matrices
are the cause of 95% death
of data visualization projects

64. Tables & Matrices
Avoid:
• Borders
• Strong Background colors
• Scrollbar (if it’s possible!)
Use Conditional Formatting
Responsibly!

65. Custom Visuals?

66. Colors

67. Colors
• Colors must have a significate
• Mind Color consistency
• Follow your artistic talent but also some designer guide!

68. Color usage

69. Color usage

70. Consistency

71. Recap

72. Welcome to
the Viz Club

73. 1st Rule
You do not use Pie Chart

74. 2nd Rule
You do not use Pie Chart

75. Less is more
Keep it
Simple!
Keep it
Clear!

76. “A report is like a joke:
If you have to explain it,
it's bad design”

77. It’s not when you have
nothing else to add,
It’s when you have
nothing to take away
Perfection

78. Bibliography
• Alberto Cairo, The Truthful Art
• Alberto Cairo, The Functional Art
• Cole Nussbaumer Knaflic, Storytelling With Data
• Stephen Few, Information Dashboard Design

79. Useful Links
• http://www.storytellingwithdata.com/
• https://www.perceptualedge.com/
• https://micoyuk.com/
• https://blog.hubspot.com/marketing/color-theory-design
• https://coolors.co/

80. Thank you!