If you torture the data long enough, it will tell you anything.
John W. Tukey
Tableau has established itself as a credible and reliable BI solution, popularly known for its ergonomic interface and advanced Tableau data visualization. Companies from all sectors are integrating Tableau to unlock hidden data insights, promote actionable decision making, and efficiently forecast upcoming market trends.
Data visualization with Tableau is very swift and doesn’t require any technical expertise.
Anyone with a basic understanding of how to use Tableau for data visualization can easily transform raw data into actionable insights. Still, there remains a slight chance of human errors that can generate misleading data visualization in Tableau. Therefore, users must be cautious and actively avoid errors when creating Tableau data visualizations.
Even a slight inconsistency or wrong inputs can generate inaccurate and confusing data insights.
10 common mistakes to avoid in Tableau data visualization projects
Mistake 1: Overloading Dashboards
Overloading the Tableau Dashboard with too many visuals, like graphics and charts, will eventually confuse and distract users. It can also cause sensory overloads and brain fog, leading to inaccurate decision-making.
Too many charts or graphs are not required at once, but their presence can hide the most important ones. Due to this, users will find it tough to derive meaningful conclusions.
Therefore, during data visualization with Tableau, it is recommended to keep the dashboard clean and clutter-free for better navigation and clarity.
Mistake 2: Using the Wrong Chart Type
Another major mistake users make during Tableau data visualization is assigning the wrong chart types. This highly distorts and misleads the audience.
Like, some users mistakenly employ a pie chart to display forecasts over time when they should have gone for a line chart. Such usage of wrong chart types can completely distort or mislead the viewers.
Hence, the users should always use only the right chart types that are most relevant to the data visualization. It will make the entire picture clear and eliminate any chances of misinterpretations.
Mistake 3: Ignoring the Audience
The data visualization in Tableau should always be done according to the interests and requirements of the audience. Like, if the data visualization is being made for non-technical viewers, then they should contain simple graphics and minimum technical jargon.
The simplicity of the graphs and visuals must be adjusted according to the audience’s
expectations rather than personal preferences. In this way, the Tableau graph visualization will be highly relevant and impactful for the viewers.
Mistake 4: Bad Color Choices
Excessive usage of bright and eye-sore colors can destroy the visual appeal and overwhelm viewers. Any bad color palettes or contrasts will also cause readability issues, limiting access to key information. Moreover, some color-blind viewers may not be able to consume the content due to bad color combinations.
It is therefore always recommended to only use universal color palettes and to cater to a wide range of viewers. The colors should always have their own purpose and must highlight or divide
content appropriately. Overall, picking the right color combinations is a must for creating satisfactory and user-friendly Tableau data visualization.
Mistake 5: No Clear Hierarchy
The Tableau Data Visualization projects should contain a clean and clear hierarchy of content. The viewers should know where to deploy their attention.
The layouts need to be effectively designed in a way that positions the most important metrics at the top while also highlighting key data segments to attract eyeballs.
Mistake 6: Skipping Data Labels & Legends
The lack of legends or data labels will make any visual meaningless and confusing. The audience will not know what these numbers showcase or what the colors signify.
To avoid such disastrous scenarios, it is crucial to always employ relevant data labels and legends. They ensure clear and effective communication of the Tableau data visualization while also eliminating the need for any guesswork.
Mistake 7: Not Testing Responsiveness
The viewers always use numerous devices of different sizes to access the Tableau data visualization. Hence, the entire project needs to be user-friendly and responsive for all types of screens.
It is crucial to first test the Tableau data visualization across several devices to verify its responsiveness. The dashboards must provide a consistent user experience across devices without distorting visuals or layouts. A user-friendly and responsive Tableau data visualization improves user accessibility and allows viewers to glance at it using any device without any visual discrepancies.
Mistake 8: Inconsistent Filters or Parameters
Using inconsistent parameters or filters will cause severe confusion and misinterpretations of the Tableau data visualization. Like, if one graph displays the right filtered content while the other mistakenly contains different filters, then the viewers will be misled by wrong data.
So, to prevent that from happening, uniform and consistent filters or parameters should be used in the entire project with correct labelling.
Mistake 9: Ignoring Interactivity
Tableau offers robust interactivity across projects using numerous actions, drill-downs, and filters. The users can navigate through the data without any hassle.
Therefore, the Tableau Data Visualization must contain these elements for efficient interactivity. Otherwise, users will be stuck at one point in the project and will not be able to engage with the other sections swiftly. Utilize relevant tooltips, legends, or filters to ensure maximum interactivity and user experience engagement.
Mistake 10: Not Reviewing Before Publishing
Before publishing any Tableau Data Visualization Project, there must be a detailed review of the entire dashboard. Sometimes, there may be typos, grammar mistakes, or broken filters that may hamper the user experience.
Therefore, a quality-assurance check is a must before making any dashboard live. Every single element, visual, color choice, or interaction needs to be rigorously tested and verified.
It will ensure that the final result is polished, credible, and user-friendly.
Final Words
“Remember, the goal of data visualization is to illuminate, not obfuscate. Keep it simple, relevant, and honest. Your audience, whether they are tech-savvy analysts or top-level executives, will thank you. After all, in the world of data, clarity is king.”
There should be an utmost priority to avoid these common Tableau Data Visualization mistakes, such as inconsistent charts, bad color choices, overwhelming interface, etc. Make sure to have a user-friendly and responsive layout. Understand what the audience expects and be consistent with those demands throughout. A reliable and credible Tableau Data Visualization Project should tell an actionable story. And, avoiding making such silly mistakes is a necessary step in achieving that.
