Charts are widely accepted elements of data visualization. In fact, advanced charting tools communicate information in a way that leads to more active engagement with your site content. Being aware of your chart readability means optimizing its format before posting on your website. Every chart should have a clear title telling your viewers what’s being measured. Good data charts also contain only the essentials to avoid complicating your data. Keep it as simple as possible. After all, you want people to understand the purpose of a study and why you chose those variables to represent your numbers. 

What are the issues that arise from unclear chart visuals?

People tend to notice visual contrast and patterns upfront. They might skim over little details or focus more on one specific element over others. This can cause a confirmation bias in their chart predictions. The root cause of confirmation bias is usually poor chart visuals.  Let’s look at an example of what not to do. Say you are plotting customer service calls against the number of outages over the course of a week. This can be is pretty confusing to decipher if you’re trying to find a common trend. Instead,  limit your graph to the calls received before during, and after one power outage. Here are the most frequent problems seen in charts:
  • Overlapping two graphics of different types 
  • Ignoring color conventions for map legends
  • Having large blocks of text as graph labels
  • Zooming in on a limited range of intervals
  • Adding abbreviations that aren’t obvious to the reader
Size is another factor to consider. If you build a bubble chart, scaling bubbles helps explain their proportions relative to each other. Don’t introduce too many variables either or your readers may experience information overload.  It cuts both ways, however. If you have several smaller charts that share the same variables, then you can fuse them into one comprehensive chart. Leaving them as stand-alone charts may obscure the meaning of the big picture. It is simply a matter of defining what you what the cart to mean and choosing the best way to present it. The goal of data visualization is all about presenting a reasonable conclusion from the information on your chart. The last thing you need is people struggling to make sense of the outcomes you want to highlight. 

What can you do to improve your charting practices? 

Maybe your charts are hard to interpret at a glance. Some of your values are too cluttered while others show conflicting results. If this happens, then identify key questions about the inner workings of your business and use your data to answer them. You can often make this happen by using fewer variables. Rather than gathering insights to fill your reports, apply data visualization practices to create performance insights that help you make informed decisions based on visible trends over a period of time.  Charts need to be correctly formatted as well. Simplify any large numbers and decimals to make them take up less space. Depending on what you are measuring, you might have to sort objects in ascending order or draw them to scale with respect to other items.  For a closer look, you can also enable interactive features like hoverable elements or the option to zoom in or out on areas of interest. Make sure you space your data markers and labels evenly so nothing overlaps.  You should always color-code different variables in your key or legend. Think of a scatter plot of multiple datasets where related points have distinct colors.  Always remember, less is more when it comes to chart design. You to present your information appealingly. You don’t want to make it confusing or disjointed, you want your users to form an educated opinion about the data. 

How do you save effort on implementing JavaScript charts? 

Most webmasters don’t want to reinvent the wheel. This is why they often rely on static chart templates to summarize their quarterly reports. A flat template, however, can’t display data collected in real-time or presented in 3D.  To make interactive viewing easier for everyone,  you’re better off installing a charting API on a JavaScript framework. JavaScript is the ideal browser and web app language, and APIs also offer advanced charting tools to help your users draw connections or find patterns in your charts. If you’re communicating data in an organized setting, you already know that data storytelling is a significant component in business decision-making, but let’s take another look. Data Visualization helps you:
  • examine the effectiveness of a new marketing strategy on your consumers
  • make informed decisions and take the appropriate actions
  • track your sales funnels, gauge customer interest, measure overhead costs, 
  • clear up any notable discrepancies and lend credibility to your meeting presentations
  • uncover the relationship between multiple sets of data for your target audience
To accomplish those feats, you need a responsive charting solution. One that gives you professional designs and faster development capabilities.  One faster and more effective than uploading to a charting API than with Office products.  FusionCharts gives you countless data visualization products and the necessary documentation to start testing demo graphs yourself. Your developers in particular will appreciate the seamless dashboard integration with their browsers or apps.  Learn about what FusionCharts can do for your business by exploring the Suite XT, FusionTime, or FusionExport charting tools. 

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