Data Visualization Tips and Tricks to Turbocharge Your Charts

Effective data visualization is important in the telling of news stories and in the field of statistics. If you want to know how to learn data visualization, then read this article for some basic data visualization techniques. Basically, what we are saying is you need to know when to use graphs, pictographs, infographics, or flowcharts.

A good example of tracking data and interpreting trends is Lake Hopatcong. Over the last 30 years, Princeton Hydro has collected surface water data. We plotted the average surface temperatures using a line chart. The figure below shows a statistically significant increasing trend in July surface water temperatures in Lake Hopatcong. This data has been linked to climate change impacts and increased harmful algal blooms. While there has been some variability, the trend is rather steady and continues to increase.

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It’s more of storytelling and conveys the idea impactfully. I use it to demonstrate data related to cost and value comparison, highlight the area of constant focus, and streamline activities. In fact, Eden Cheng of PeopleFinderFree says, “My personal https://globalcloudteam.com/ favorite is the bubble chart. It looks attractive and displays information in a very impressive way. Here, the weight of the value is defined by the bubble circumference. So, one can easily spot which factor is important and which is not.

To put in other words, a dashboard helps to visualize figures related to sales, production, efficiency, planning, client satisfaction level or key market trends. There are many methods to visualize data, new solutions and chart types come out constantly, and each strives to create more attractive and informative charts than before. You need to select the suitable type that best suits your need. Edraw data visualization software helps you produce over 200 kinds of visuals instantly.

We’ll cover examples of the most effective data visualization charts below. Nearly every profession can benefit from data being broken down in simpler terms. Data visualization takes complex data and makes it easier to understand for those on the receiving end through the use of infographics, pictographs, and other charts. By presenting data in bite-size chunks, those complex numbers become more easily digestible. With a strong presentation software— like Beautiful.ai— it’s easy for non-designers, and non-analytical people, to make sense of data for themselves and their audiences. It is difficult to identify trends by just looking at the raw data, and frankly it can be overwhelming if you’ve collected a lot of information.

Since the purpose of data visualization is to show your data, keeping your text to a minimum can help the data be easier to interpret. To avoid this, keep your visuals as simple and clear as possible. Favor streamlined ways of presenting data, even when that means using more than one chart or graph. You can also use interactive data visualization techniques to allow users to play around with the data and instinctively discover it.

of the best data visualization examples from history to today

Understand which plots are commonly used in the industry you are working in. To conquer this roadblock, a presenter needs to understand the power of data visualization techniques. Key is start using data visualization tricks to make figures or data easily comprehensible even for an ordinary audience. Creating charts and infographics can be time-consuming. Edraw is the optimal tool to create stunning visualizations with ease. It is a fast, flexible charting solution that allows users to explore and interpret dense data sets.

• This applies both to the dashboard design as well as the individual chart level.
• Order categories alphabetically, sequentially, or by value.
• See for yourself how fast and easy it is to create visualizations, build dashboards, and unmask valuable insights in your data.
• To see the power of data visualization at work, watch this quick video.
• Upgrade your data visualization software to a smart tool like Polymer, that can toggle between different visualization options, and automatically adapts to a mobile or PC setting.
• If you’re working with temperatures, use red to indicate heat and blue for cold.

Either way, the data is the data, and it is up to you to tell the story of this newly analyzed information. If you still need a little help with your data storytelling, don’t be afraid to seek outside help. Here are a few tips to find the right data visualization agency, as well as tips to work together once you do.

Take your data visualization to a whole new level

Instead of using fancy and complex graphs, favor using simpler data visualization techniques, and using the right tools to keep your data fluid and flexible. This starts by having a goal in mind and then working backwards to identify the number of charts and different formats you need. The final version can be shared as a report or a dashboard. Sometimes even combining related charts is helpful; it can fuel deeper exploration that leads to helpful business insights and answers that drive action.

Keeping your slides clean and simplistic is key for data visualization if you want your audience to retain any of the information you’re presenting to them. Each slide should feature one key takeaway, and it should be obvious to your audience— don’t send them on an easter egg hunt to figure it out. Data visualization is deceptively complex, especially when you don’t have the right visuals or the tools to create them. Fortunately, nowadays with interactive data software and robust AI-powered tools, interacting with and expressing your data is becoming easier than ever. When designing different charts and graphs, it’s easy to get carried away and overdesign or overshare data.

Box and Whisker Plots

Good visualizations explain complex and complicated stories with simple graphics, charts, and visuals. More importantly, they help organizations clarify and pinpoint business issues they need to resolve. This is because a well-designed visual has the capability to efficiently and economically communicate more information than a table or a raw piece of text. Simply put, visuals are more effective than tables at presenting data. I have found that different forms of visual charts serve different purposes.

If you are depicting sales month by month on a bar chart, use a single color. But if you are comparing last year’s sales to this year’s sales in a grouped chart, you should use a different color for each year. You can also use an accent color to highlight a significant data point. When what is big data visualization used poorly, it can not just distract but misdirect the reader. Data visualization design is both an art and a science, which is why it can be challenging for noobs to master. But if you want to master data storytelling—and make a strong impact through content—it’s a crucial skill.

Step 1: Organize Your Data

If you are trying to differentiate, say, on a map, use different saturations of the same color. If the copy already mentions a fact, the subhead, callout, and chart header don’t have to reiterate it. Showing that you’ve actually had a 100% sales increase since Q1. The box and whisker plot, also known as a box plot, is used to show the average value and first and third quartiles of categorical data. A box plot shows if the data is distributed evenly, or if it is skewed.

San serif fonts such as Century Gothic is a good candidate. Besides, using a suitable color palette is important. Color is proved to enhance attraction and communication effectiveness. I usually use ColorBrewer to choose color for my visuals to avoid color blindness and achieve friendly print. This version not only gets rid of above issues but also sticks to the third rule of “data emphasize, not visualization”.

Tips for creating effective, engaging data visualisations

Don’t use clashing colors or textures that are difficult to look at. Keeping data visualizations simple and digestible is the only way to get your point across without losing your reader. If you create a graphic that is too complicated or busy, the reader won’t be able to figure out what you are trying to communicate.

Instead of using colour, shape size can adjust based on data values. Use intuitive colours that make sense to the viewer so they process the information faster. Bar charts are effective at comparing categories within a single measure and one of the most common data visualisations. An automobile dashboard provides information about various parameters of vehicles. In the business world, it can be applied as a metaphor of Key Performance Indicator .

14) Make sure there is sufficient contrast between colors. If colors are too similar (light gray vs. light, light gray), it can be hard to tell the difference. Conversely, don’t use high-contrast color combinations such as red/green or blue/yellow. Don’t use red for positive numbers or green for negative numbers.

The Power of Data Visualization

If you are focusing on the data of a specific period, remove the data of other periods. Canva.com’s interactive tool on color meanings and symbolism. Long format is generally considered the standard data entry format, and some statistical programs require data to be entered in long format. Order categories alphabetically, sequentially, or by value. Readers rely on labels to interpret data, but too many or too few can interfere. Stripes and polka dots sound fun, but they can be incredibly distracting.

Firstly, we should reduce mental tasks because the more people have to interpret data, the slower they understand the data. Data visualization is how you avoid situations like these. In this post, we’re going to be looking at the concept of data visualization and other interesting discussions that surround it. Try Tableau for free to create beautiful visualizations with your data. Just like a bar chart, the line chart expresses values on an x and y axes but connects them together into a line.

We suggest using different colors to provide contrast between data sets. Use your boldest colors to represent the more important pieces of information, and more subtle hues to indicate the rest. While your colors should be on-brand and consistent with the rest of your presentation, it’s okay to play around with different hues here. Colors are an easy way to tell the audience exactly what you want them to pay attention to, and how it should make them feel. Data storytelling is how you choose to communicate your insights to make them more meaningful and relevant to your audience, and can be used to support your overarching message.

There are many online data visualization courses for you to learn effective data visualization techniques. Coursera is a great place to look for online data visualization courses. Bullet graphs are an effective visualization tool for businesses to view financial performance compared to their targets. The target is represented by a vertical line on a scale of values.