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Workshop Title: “Building Clear, Persuasive Charts”

Date Time: From

Fri, Jun 2, 2023

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14:00

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14:00

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Location:

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Time Limit:

-

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Benefits

The target audience

Better work quality

Career

The Organization

The Speaker

Speaker Credibility

Audience Analysis

Producers, 8x-9x

Not confident in data and data viz

Aspirations?

Motivation to Join?

Audience Transformation

Domain

BEFORE

AFTER

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.

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!

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.

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

There are no rows in this table

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