DATA ANALYTICS

3 Data Visualization Techniques Everyone Should Know

Devon Tackels

Content Marketing Manager, Sigma

Have you ever looked at a data set and thought to yourself, “How can I visualize this?” Unfortunately, that’s a lot like asking, “How many ways are there to make a buck?” The answer is…a ton. The good news? There are enough data visualization techniques to tell any story. 

When it comes to visualizing data, there’s no such thing as one size fits all. There are many ways to visualize data, but you don’t have to have a Ph.D. in Data Science or learn how to create deep visualizations to tell a data story.

Whether you want to use data visualization to understand the effectiveness of your marketing campaigns, pinpoint emerging trends, or build the perfect dashboard, there are three simple approaches that will generally work most of the time.

But whichever data visualization technique you choose should be influenced by five core factors — your audience, the type of data, the context, dynamics, and its overall purpose. Let’s take a closer look at each.

Considerations for choosing a data visualization technique

Audience

Are you creating a visualization that consumers will use to chart their monthly spending habits? If so, you’ll want to keep things as simple as possible. But, if you’re tracking the annual expenses of a multi-billion dollar global conglomerate to report to the board of directors, you want to kick things up a notch. Choosing the best visualization medium starts with assessing the needs of your viewer.

Content

What type of data do you want to visualize? Some types automatically lend themselves to specific formats. For instance, if you’re going to highlight the most searched terms on Google in the past year, you’d opt for a word cloud chart. On the other hand, to visualize the popularity of different music genres throughout history, an area chart may be the way to go. The type of data heavily influences the technique.

Context

You can’t just display your data and leave it up to the audience to figure out what it means. Context is everything. What is the overarching story you want to tell? How can you best visualize the data to answer your viewers’ burning questions? And what other elements can you add to provide context? Options include a legend, color, captions, and comparisons.

Dynamics

Is your data static or variable? If the latter is true, go for a dynamic visual representation displaying your data in real time for the most accurate illustration.

Purpose 

Without a goal, you can’t score. And without knowing what you want to achieve with your visualization, you are highly unlikely to gain anything of value. Start with the end in mind, using the purpose of your visualization to influence the way you ultimately implement it.

Now that we’ve got the criteria for selecting a data visualization technique out of the way, let’s dig into the three types every data analyst should know.

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Common data visualization techniques to know

 Charts & Graphs

Admittedly, bar charts are boring. And you may be thinking, “In a world where there is an unlimited number of ice cream flavors, why would I choose vanilla?” Well, because it works. And if it ain’t broke, don’t fix it.

Charts and graphs aren’t sexy, but they are effective. So, if your data works well in a bar chart, use the bar chart. Remember to keep your audience in mind. Who hasn’t seen a chart? We’re taught in grade school to understand how they work to tell a data story. They’re easy to process and help viewers to understand the data quickly.

And, while there are many different flavors of charts and graphs, stick with whichever one gets you closer to your goal the fastest.

Common types of charts and graphs include line graphs, bar graphs, histograms, pie charts. 

 Diagrams

Whether your data is hierarchical or multidimensional, a diagram will help you to demonstrate complex data relationships. Consider using a network diagram to analyze social networks to understand your organization’s interactions with its customers.

Who did your company mention, follow, or send a direct message, and what hashtags did they use? A carefully constructed diagram can help your sales, marketing, and customer service teams assess their performance and create a plan of action.

Try using a network diagram, tree diagram, or block diagram to visualize your data.

 Maps

If you want to visualize geographic data by location — for example, to compare your company’s sales across different regions — using a map is a no-brainer.

While most people understand maps, if location isn’t an integral piece of your data puzzle, don’t use a map. Also, avoid the urge to throw a million data points up on a map and walk away. It’ll only serve to confuse the audience. Instead, include enough points to illustrate your data story effectively.

Point maps, line maps, flow maps, and heat maps are just a few of the options available to you.

Craving more? Check out Data Visualization – The Definitive Guide to discover the 21 most common data visualization techniques.

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Storytelling with data visualization

Data visualization is a critical weapon in every team’s arsenal. It helps to empower all stakeholders with actionable information by breaking down massive amounts of data into an easily digestible visual representation. But even seasoned data aficionados must face the challenge of how to strategically present data to your audience.

There’s no such thing as a gold standard for data visualization. The technique you employ should always depend on the type of data, your audience, and the insights you want to extract. Don’t be afraid to visualize your data in a few different ways until you find the technique that works on every level.

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