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Summary
How to bring data visualization best practices into your products, from dashboards to reports to BI tools. Learn about which charts to use when, creating accessible color palettes, and preview some new visualizations Theresa Neil has been testing in enterprise organizations.
Key Insights
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Begin by understanding the user needs behind data requests rather than just the data itself.
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Identify whether a dashboard should be exploratory or explanatory to guide the design process.
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Chart types should match the questions users are asking, with a focus on familiarity and usability.
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Avoid reliance on flashy designs; prioritize clarity and accuracy of information presented.
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Storytelling can transform dashboards by providing context to data and enhancing understanding.
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Accessibility in data visualization means choosing color palettes that work for all users, including those with color blindness.
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Collaboration with stakeholders can lead to more informed decisions regarding dashboard design.
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User testing is critical, as many people struggle to interpret even basic charts correctly.
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A structured approach to design ensures that the right metrics are prominently featured without overwhelming users with information.
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Continuous feedback loops with users can lead to improved design iterations and better product outcomes.
Notable Quotes
"I woke up at 3:30 this morning thinking about all of the cool things I wanted to share about data visualization."
"The simplest request from anyone I’ve worked with is just make me a dashboard."
"The real question is who's going to be using this?"
"If you're looking to up-level database in your organization, start with the users, not the data."
"Sometimes, charts are not the answer; sometimes a single number tells the story."
"Color tells you where to look; it’s crucial to use color intentionally in data visualizations."
"Marketing style guides often clash with data visualization needs; you need palettes that serve data, not marketing."
"The first rule of data visualization is clarity; it’s not about making things look sexy."
"You need to create multiple color palettes for different data visualization types."
"A good portfolio of accessible colors can help convey positive and negative data without overwhelming traditional color cues."
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