05 December, 2024
Psychology of Colours in Data Visualisation
How are you using colours in your data visualisations?
Reading time 5 minutes
Hello!
Hope you all survived Black Friday and are now on that countdown for Christmas. Does anyone know where 2024 disappear to?! This week we have a few top tips for features in Power BI you should be using along with some useful information on using colours in your data visualisations.
Power BI is a powerhouse for data analytics, but many users barely scratch the surface of its capabilities. Here are ten hidden features you might not be using—but should—to transform your data analysis workflow.
Power BI’s Q&A feature allows you to type natural language questions directly into the dashboard. For example, “Show total sales by month” instantly creates a visual without manual effort. It’s a fast way to explore your data intuitively.
With Smart Narratives, Power BI automatically generates textual insights based on your visuals. This is especially useful for stakeholders who prefer written context alongside charts and graphs.
Bookmarks enable you to save specific views of your reports, including applied filters and selected visuals. This makes presenting different scenarios or perspectives during a meeting seamless.
This feature lets users click on a specific data point and navigate to a page with detailed insights about it. Perfect for understanding granular trends behind summary data.
Power BI allows you to import custom visuals from the marketplace. If your default visualisations feel limiting, explore unique visuals like bullet charts, Sankey diagrams, or timeline slicers.
Conditional formatting is more than colour-coding rows. In Power BI, you can use data bars, icons, and even gradient backgrounds to highlight key insights visually.
Not a DAX expert? Use Quick Measures to create common calculations like running totals, rank, or variance with just a few clicks.
For datasets with millions of rows, incremental refresh saves processing time by only refreshing new or changed data. It’s a game-changer for large-scale projects.
Combine data from DirectQuery and Import modes in a single report. This hybrid approach allows you to work with real-time data without sacrificing performance for static data sources.
Power BI isn’t limited to dashboards. Use Paginated Reports for printable, pixel-perfect layouts—ideal for financial statements or formal reporting.
Unlock These Features Today
These hidden tools can transform how you interact with data. Experiment with one or two features in your next project and see how they elevate your analysis.
Colours in data visualisation do more than decorate—they shape perception, focus attention, and clarify insights. When used strategically, colours help audiences quickly interpret complex data. Misused, however, they can cause confusion or mislead. Here’s how to harness the psychology of colours to enhance your visuals.
Colour psychology taps into our subconscious associations. For example:
Red and Orange: These warm tones evoke urgency or caution. In charts showing deadlines or risks, red immediately signals areas requiring attention.
Blue and Green: Cool hues are calming and suggest trust. They are often used in financial or healthcare dashboards to foster confidence in data integrity.
Example: A company tracking workplace incidents might use red to highlight departments with higher risks and green for those meeting safety standards.
Selecting an appropriate colour scheme depends on the type of data:
Categorical Data: Use distinct, contrasting colours to separate categories clearly. For instance, a bar chart comparing revenue streams by product line should assign a unique hue to each product, avoiding overlap that could blur distinctions.
Sequential Data: Gradients of a single colour work best to show a range, like heat maps for population density. Lighter shades signify smaller values, while darker shades indicate higher concentrations.
Diverging Data: When visualising data with a midpoint (e.g., profit/loss), use two opposing colours like blue and orange, with a neutral colour such as grey at the centre.
Example: In a profit and loss statement, blue can represent gains, orange can highlight losses, and grey can show break-even points.
Approximately 8% of men and 0.5% of women experience colour blindness, with red-green being the most common. Without consideration, your visualisations might exclude these viewers. To create inclusive designs:
Avoid problematic combinations like red and green.
Use tools like Coolors or Power BI’s accessibility checker to test your palettes.
Incorporate patterns or labels alongside colours for clarity.
Example: An election map could use blue and orange patterns instead of traditional red and green to ensure all viewers can distinguish results.
When designing visuals, keep these guidelines in mind:
Don’t Overload with Colours: Too many colours can overwhelm and distract. Stick to 3–5 tones for consistency.
Highlight Key Data Points: Use bold or bright colours sparingly to emphasise critical information.
Consistency is Key: Maintain a consistent palette across all charts to build familiarity and focus.
For instance, a dashboard summarising sales performance might use shades of green for growth metrics and shades of red for declining trends, reinforcing the narrative.
Colours in data visualisation are more than aesthetic choices—they are storytelling tools. By understanding the psychology of colours, selecting the right palettes, and designing inclusively, you can transform your visualisations into powerful narratives. Next time you create a chart or dashboard, remember: colours should do more than catch the eye; they should drive understanding.
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