Your client says your data visualizations are too complex. How do you simplify them?
When your client finds your data visualizations too complex, it's essential to simplify them without losing key insights. Here's how you can refine your approach:
What strategies do you use to simplify data visualizations?
Your client says your data visualizations are too complex. How do you simplify them?
When your client finds your data visualizations too complex, it's essential to simplify them without losing key insights. Here's how you can refine your approach:
What strategies do you use to simplify data visualizations?
-
Few ways to simplify a complex dashboard is to avoid cluttering with too many visuals/graphs and avoid too many tables. Simplify filters and add tool tips. Provide drill down and interactivity. Have some white spaces so that the dashboard looks neat and appealing. Use consistent colours and fonts. Get consistent feedback from the end users and improvise making the dashboard intuitive. Ensure the dashboard layout looks aligned in any device the user views it. Most importantly, focus on the necessary KPIâs and remove unwanted information.
-
One way not to loose your client with your visualisations is to ensure that they tell a story. To do that, your visualizations must answer these three questions 1. What>>> do the visuals say what is happening 2. So what>>> implications 3. Now what>>> how do we change the tides.
-
Data visualization should enhance your message and add meaning to your data. Therefore, it's essential to understand what you are presenting, how you are presenting it, and to whom. Using expert-recommended charts can simplify complex information. For instance, use bar charts for comparative analysis, line charts for trend analysis, pie charts for displaying data in percentages, and tables for detailed data. One can further improve reports by incorporating navigation elements, interactive features, tooltips, and more. Power BI offers excellent options for enhancing the end-user experience, such as custom tooltips, Q&A capabilities, and narrative elements.
-
The important thing is to simplify the visualization without losing insights. It can be done by some steps: ⢠Understand the audience: Tailor your visuals to their knowledge level. ⢠Focus on key insights. ⢠Choose the right chart. ⢠Incorporate Storytelling: Guide your audience step-by-step through the data.
-
Simplifying data visualizations is about enabling decisions, not just sharing data. Iâve found that asking, âWhatâs the most important takeaway?â helps focus on key insights while eliminating unnecessary clutter. Understanding the audienceâs needs is also crucialâwhatâs clear to one group might overwhelm another. For me, storytelling is a game-changer; guiding viewers through the data with annotations and a logical flow ensures clarity and engagement. Simplifying doesnât mean oversimplifyingâitâs about creating visuals that are as impactful as they are clear.
Rate this article
More relevant reading
-
Statistical Data AnalysisHow do you communicate and visualize your time series analysis and forecasting results to stakeholders?
-
Product DevelopmentHow can you use data and analytics to support your pitch without overwhelming stakeholders?
-
KPI DashboardsHow do you incorporate feedback and interactivity into your dashboard story?
-
Business IntelligenceHow can you present data insights to senior executives and decision-makers with confidence?