How to choose the Better Graph For Data Visualization?

How to choose better graph for Data Visualization - Thinklytics

Are you not sure about choosing a better graph for data visualization to effectively present your data? What about a pie chart, bubble chart, or scatter plot? Is there a better way to communicate your information? Obviously, you may not be aware of it.

Quite often, you waste your time and effort using the wrong chart or graph. Moreover, your readers may have a hard time understanding what you’re trying to convey. The art of data visualization goes beyond converting set of data into graphs and charts.

Getting Started with understanding a better graph for Data Visualization

At Thinklytics, we have experts engaged in visualizing your data stories. We help our users share their insights and ideas through infographics. Also, we’re on a mission to rid the world of data visualization gone wrong.

Not all data visualization superheroes wear capes, though. Sometimes, they use the power of words. The write guides and how to blog to help you choose the better graph for data visualization.

Buckle up as we walk you through the common types of charts and graphs and use a specific format and design. We will also discuss best practices to help your reader easily grasp and understand your information.

Need to choose the right data visualization format

Your brain is more likely to synthesize and retain visual data. After all, visual content is the way to your audience’s hearts. It explains the utility of charts, graphs, and infographics to show trends, summarising stats, and telling stories.

But if your information isn’t correctly visualized or designed, there’s a good chance that it can do more damage than good. The incorrect data visualization format can either completely misrepresent your data or reduce the effectiveness of your message.

Points to consider while picking a graph for data visualization

If you’re unsure about the best type of visual that will convey your message effectively, your first step is to think of the big picture. Then, ask yourself the following questions, which will help you decide on the best visualization technique.

1. Who do you want to share it with?

Knowing your audience will help you determine the best way to visualize. For example, what is their level of understanding or knowledge? Which data visualization formats are they familiar with? For example, it makes little sense to create complex graphs or charts. Instead, consider pictographs or simple charts.

2. What are you trying to accomplish?

Before you work with your data, figure out your goal. Why are you doing this? Do you want to inform your readers? Or do you want to convince them with your data? What is your purpose? Whether you use data to derive insights or predict sales and purchases? The reason for visualization is again essential.

3. What story in your data do you want to share?

What’s the main idea? It is where you search for important insights or interesting patterns in your data points. For example, do you want to illustrate a comparison? Or highlight a trend? Knowing your main idea will make it easier to choose the proper visualization format to deliver your message effectively.

4. Where will you publish your data?

Think about your preferred platform. For example, if you’re an online marketer, how will you drive traffic to it? Whether you’re considering publishing your graph in an email newsletter or uploading it on your blog, knowing your platform beforehand will help you decide which presentation formation is the most ideal.

5. Are you using too much data?

There’s no doubt that we’re in the age of Big Data. But this doesn’t permit us to douse ourselves with data. It will be inappropriate to use data in every way possible. Develop an eye for clarity by knowing which data point is essential (and which ones to get rid of) for an engaging data visualization piece.

6. What type of data do you want to present?

Data comes in various types. In data visualization, you’re most likely to encounter the following types: Quantitative and Qualitative data. Since each type of data has to be represented differently. Hence, choosing the right chart or graph will help you convey the correct message to your viewers.

In a nutshell, your data visualization goals can be narrowed down to:

  1. Inform your audience of a specific data point or numerical value.
  2. Highlight a comparison or show a composition.
  3. Demonstrate change over time or location.
  4. Compare different categories or highlight rankings.
  5. Highlight relationships like distribution, correlation, deviation, and distribution

Different Types Of Charts That Can Be Used For Visualization

Bar chart: This can be used to compare parts of a whole, highlight different categories, or show changes over time. They are also available in different styles –

  • Vertical bar chart or column chart
  • Horizontal bar graph
  • Stacked bar chart

You can highlight a specific figure, such as total sales. It is the easiest tool to make and quickest to understand. Always have a zero baseline to avoid getting a false visual comparison.

Different Charts for Data Visualization

Line graph: This type of graph is best for displaying a data series. The most significant advantage of line charts is using multiple data series and data points. Make sure that your points are ordered. e.g, time runs from left to right.

Area chart: Area charts are similar to line charts because they can also depict time-series relationships, but they’re also different as they can portray volume. Avoid using area charts to illustrate discrete data.

Pie chart: Illustrates simple part-to-whole relationships of discrete or continuous data. The total value is placed at the center. Pie charts are not the best data visualization type to make precise comparisons. Hence, keep in mind to review if your data adds up to 100 percent.

Scatter Plots: These are used to highlight the correlation and distribution of large amounts of data. Do not use scatter plots when you have only a few pieces of data or if your data doesn’t show any correlation. Data sets should be in pairs with independent (x-axis) variables and dependent variables (y-axis).

How to choose the Better Graph For Data Visualization? - Infographic

Now, it’s your turn to adopt data visualization

Finally, complex charts will eventually confuse your audience rather than impress them. So, it’s your turn to make your chart that will best deliver your message! Thinklytics is always ready to help you out with the best data visualizations to help your business grow at a higher pace.

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