Common Tableau Mistakes and How to Avoid Them
Tableau is a powerful tool for data visualisation, however poor design choices and performance oversights can diminish the impact of a dashboards, as well as create misinterpretation and frustration. Below, we explore some common pitfalls in Tableau and offer practical solutions to avoid them.
Clean and clear goes a long way to creating a great dashboard
1. Overloading Dashboards with Excessive Data
The Mistake: One of the most common issues with Tableau dashboards is data overload. Many users attempt to cram as much data as possible into a single dashboard, believing this provides a comprehensive view. However, an overpacked dashboard can lead to confusion, as the viewer struggles to sift through multiple graphs, charts, and tables simultaneously.
How to Avoid It: Prioritise clarity and simplicity. Ask yourself, “What are the key insights I want to communicate?” For each visual element, consider if it adds value to the core message or just serves as a distraction. If you need to show a lot of data, use a storytelling approach by creating a series of dashboards with a clear navigation path.
2. Ignoring Performance Optimisation
The Mistake: Tableau’s performance can slow down considerably when dealing with large datasets or complex calculations. Slow dashboards frustrate users and diminish engagement.
How to Avoid It: Optimising performance should be a priority, especially with larger datasets. Here are a few strategies to consider:
Extracts Over Live Connections: Use extracts instead of live connections where possible, as they reduce load time by working with a static snapshot of the data.
Reduce Unnecessary Calculations: Complex calculations can slow down processing. Simplify calculations where possible and use aggregated fields to limit the data processing required.
Minimise the Number of Visualisations: Each visualisation requires computational power. Focus on essential charts, and if you need multiple visuals, consider adding them as separate sheets rather than combining them on a single dashboard.
3. Using Misleading Visualisations
The Mistake: Misleading visualisations are typically unintentional but can significantly skew perception. Examples include using inconsistent axis scales, inappropriate chart types, or excessive use of colour. These choices can create confusion or present data inaccurately.
How to Avoid It: Choose the right visualisation for the data and maintain consistency in scale and design. Avoid chart types that overcomplicate the story, such as 3D visuals or stacked bar charts with too many segments.
4. Neglecting Mobile Responsiveness
The Mistake: Many Tableau users design dashboards only with desktop displays in mind. However, as mobile and tablet use increases, overlooking mobile optimisation can lead to a poor experience for users accessing dashboards on smaller screens.
How to Avoid It: Tableau’s Device Designer feature allows you to create responsive dashboards for different screen sizes. Design a version specifically for mobile, focusing on a simplified layout with only the essential elements visible. Test how the dashboard looks and feels on multiple devices, making adjustments to font size, spacing, and interactivity as needed to ensure accessibility across platforms.
5. Failing to Consider User Interactivity
The Mistake: Interactivity is one of Tableau’s greatest strengths, but it can be a double-edged sword. Too little interactivity and the dashboard becomes static and less engaging; too much interactivity and it risks confusing the user.
How to Avoid It: Balance is key. Identify the most useful interactive elements for your users and prioritise these. Examples of good interactivity include filters for date ranges, geographic regions, or product categories. Avoid overloading the dashboard with too many filters, and consider using action filters, which allow users to click on one chart to filter another, creating an intuitive flow. Tooltips should also be informative yet concise, providing additional context without overwhelming detail.
6. Overcomplicating Calculated Fields
The Mistake: Calculated fields are incredibly useful in Tableau, allowing for advanced data manipulation directly within the platform. However, overly complex calculations can lead to performance issues and even inaccuracies if not properly handled.
How to Avoid It: Always start by validating your calculated fields to ensure they produce the expected results. If you’re working with complicated calculations, consider breaking them down into multiple steps. Tableau allows for “Level of Detail” (LOD) expressions, which can simplify complex calculations by specifying the level at which you want to aggregate data. Use LODs thoughtfully, as they can also impact performance if used excessively.
7. Ignoring Colour Theory
The Mistake: Colour is a powerful tool in data visualisation, but misusing it can confuse or mislead. Common mistakes include using too many colours, choosing clashing colour schemes, or not making distinctions clear for users with colour vision deficiencies.
How to Avoid It: Ensure your colours enhance, rather than distract from, the data story. Use a limited palette to keep the dashboard visually cohesive, and avoid using red and green together, as they are difficult to distinguish for colour-blind users. Tableau offers a selection of colourblind-friendly palettes, which can be accessed through the Colour dropdown menu.
8. Misconfiguring Filters and Parameters
The Mistake: Filters and parameters help personalise the dashboard for users, but improper configuration can lead to confusing results. For example, using too many filters can slow performance and make the dashboard appear cluttered. Similarly, misconfigured parameters can produce errors or misleading data outputs.
How to Avoid It: Choose filters strategically. Limit the number of filters displayed on a single dashboard and use cascading filters (filters that only show options based on previous selections) to guide users through the data logically. Parameters should be set up with clear labels and should only be included if they genuinely add value. Consider default settings for filters and parameters that align with the most commonly viewed data, as this reduces unnecessary clicks.
9. Not Labelling Axes and Data Points Clearly
The Mistake: Tableau’s default settings often provide only minimal labelling, which can lead to ambiguity, especially for complex graphs. Missing axis labels, unclear headers, or lack of data point annotations can make a dashboard hard to interpret.
How to Avoid It: Invest time in making sure every aspect of your dashboard is clearly labelled and provides context at a glance. Consider adding axis labels for both the x and y-axes, provide descriptive headers, and use data labels for key values where appropriate. Text boxes or annotations for important insights can give additional context.
10. Overlooking Documentation and User Guidance
The Mistake: Often, dashboards are handed over to users without much guidance on how to interact with them. Without any documentation or instructions, users may miss valuable insights or become frustrated trying to navigate complex visuals.
How to Avoid It: Include an introductory slide, tooltip, or documentation link that provides a quick walkthrough of the dashboard’s features. This can be especially useful for dashboards with custom interactions or advanced filtering. Even a small “Help” button with brief instructions can go a long way in enhancing the user experience and ensuring that the dashboard’s value is maximised.