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1: Dashboard Design Principles
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2: Choosing the Right Chart
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3: Organizing Charts
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4: Telling Stories With Data
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5: Formatting Dashboards
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6: Legibility
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7: Interactivity
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8: Filtering
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Filtering controls what data people see when they open and interact with a dashboard. Good filtering makes dashboards feel focused. Bad filtering can make them feel confusing or broken – especially to people who haven't used filters before.
The idea is to show the right data by default while still allowing flexibility.
If users constantly have to fix filters, the dashboard is doing too much.
Report-level filters apply to every page in a report. These are useful when:
Examples include filtering to a single year or excluding test data.
Page-level filters apply only to the current page. These work well when:
Visual-level filters affect only one visual. These are helpful when:
Visual-level filters are powerful, but easy to forget. Always document or label them clearly!
Filters are not just about interaction; they also define first impressions.
A dashboard should open in a clean, intentional state:
Let's apply different types of filters to understand how they work.
This page-level filter ensures the dashboard only shows discounted sales, which can be useful for analyzing promotion effectiveness.
Top N filters are great for focusing attention on what matters most without cluttering the visual with every category.
Notice how the page-level filter (discounted sales only) affects all visuals, while the visual-level filter (Top 3 categories) only affects the bar chart. Understanding this hierarchy is key to building effective dashboards.
Save the project and, from the course directory, submit the CLI tests.