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Workshop Title: “Building Clear, Persuasive Charts”

Date Time: From
Fri, Jun 2, 2023
​14:00
to
​14:00
Location:
Time Limit:
-

Benefits

The target audience

Better work quality
Career

The Organization

B

The Speaker

C

Speaker Credibility

D



Audience Analysis

Producers, 8x-9x
Not confident in data and data viz
Aspirations?
Motivation to Join?

Audience Transformation

Domain
BEFORE
AFTER
1
KNOW
Occasionally presenting bad data visualiaztion:
😱 wrong conclusion,
🙁 wrong type,
😵 unclear and/or confusing, not persuasive
Build Charts with
Default (non optimal) options
Low Data-Ink ratio
No Process
Do not recognize the goodness/badness of charts in different situations
Create charts that are persuasive, easy to understand in Product Reviews and important Pitches, themselves. Use Tables effectively, when appropriate.
Always look for suspicious signs of wrong, non-trustworthy data visualization. And being ethical themselves.
2
BELIEVE
Powerless - because don’t know how to do it
Frustrated - because dependent on tool/someone else
Inspired - There’s so much depth!
Empowered - huh I can do it good enough! And I am not as easy to be manipulated!
3
FEEL
Data Visualization Skills is big and hard
The time and effort required to tweak the charts are not worth it
Data Analysis & Visualization is Data Analyst/BI responsibility
Showing more data is better

The difficult part is Thinking → Prod can and should do that
It relatively easy to go from bad chart to an effective chart, Prod can do it in Excel.
When exploring, more data is better. When Persuading, more focus is better.
4
DO
Meanings of Important KPI and data
How to read charts
How to build basic charts in Excel (Pie, Bar, Line) from DA’s data
The Process to make a good data visualization: Purpose → Conversation → Sketch → Prototype → Polish
How to Polish: Hone Idea - Make Stand out - Adjust Surrounding
The most common “Lie with Statistic” crime: truncated axis, scaled axis, cherry-pick data, ditch convention

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