Session
Accidental Data Lies: How Poor Visual Choices Can Mislead
Welcome to the world of accidental data lies, where innocent-looking charts quietly twist the truth. And in today’s world, where ethical data visualisation is a hot (and important) topic, it's something we all need to watch out for.
We’ll uncover the most common (and sneaky!) ways charts mislead, from pie chart pandemonium to axis trickery, colour chaos, and the dreaded “average of averages.” Expect real-world examples of chart crimes, a few laughs at visual disasters, and sharper instincts for spotting deception.
But it’s not just about dodgy design, this session also dives into the ethics of visual storytelling. We’ll explore how the ‘framing effect’ and ‘sampling bias’ can quietly distort meaning, and how to design with integrity so visuals inform rather than mislead.
From spreadsheet wizards to Power BI spellcasters, this session will help you create visuals that don’t just dazzle, they tell the truth and earn trust.
Learning Outcomes:
1. Spot the Sneaky Stuff:
Identify the most common ways charts mislead, including bad chart types, distorted axes, and overloaded visuals, and understand why they’re so effective at fooling us.
2. Choose the Right Chart for the Right Story:
Learn how to match chart types to data types, avoid common mismatches (like line charts for categories), and use Power BI visuals with purpose and clarity.
3. Design with Integrity:
Apply practical Power BI techniques to simplify dashboards, label data clearly, and communicate insights with transparency and trust.

Juliana Smith
Reporting Lead & Accessible Design Specialist
Manchester, United Kingdom
Links
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