Data, data, data!

For some, it’s just a messy jumble of numbers they’d rather avoid. But let’s be real—data is king! It’s essential for making strategic decisions that drive your business forward.

What you might need is a smarter way to make sense of all that complex data. Enter: interactive data visualization! This method presents data through charts, graphs, and maps in a way that’s not only easy to understand but also fun to interact with.

In this guide, we’ll cover:

• What interactive data visualization is all about
• The key benefits of using interactive data visualization
• Techniques for effective interactive data visualization
• Tools to help you create stunning interactive visualizations

And more!

Let’s dive in!

What is interactive data visualization?

Interactive data visualization is a form of visual representation of data that lets users explore and interact with it for better understanding.

Kirti Sharma, manager of data visualization services at Corporate Renaissance Group, defines it this way:

“Interactive data visualization uses software to show your data in ways that you can control. Think clickable charts, maps that change with a filter, and dashboards that update in real-time.”

Essentially, it involves transforming static charts or graphs into engaging versions where you can zoom in, hover, click, or filter data for more details instead of just looking at data.

This way, your complex data or numbers are presented to people artistically and appealingly. 

An example of interactive data visualization is this one by Intralinks, an inter-enterprise content management system. 

The chart shows their predictions for year-on-year deal flows for private equity across different regions. 

So instead of static charts, they used an interactive one where users click on the regions covered to see YoY changes. Creating charts this way helps simplify the data and keeps users engaged while viewing. 

Now, let’s show you other ways interactive data visualizations are helpful below.

What are the benefits of interactive data visualization?

Kirti Sharma, a data visualization specialist, has led different business analyst teams in implementing BI solutions across different domains.  In her article on interactive data visualization, she noted its role in turning raw data into insights. 

According to her, this content format is important because it helps:

• Users understand data faster. Humans are visual creatures. We tend to understand stuff like complex data and take action faster if it's presented in a relatable visual format. It makes it easy to understand. Plus, users can identify trends faster without racking their brains as it’s easy to make the connections. 
• Users can explore data in more detail. In most cases, complex data require an analyst to explain the data to viewers. However, with interactive visualizations, users don’t require an analyst or IT support to conduct deep analysis. The charts are appealing to see and have supporting information to provide context to viewers. 
• Encourages quick decision-making. Because these interactive visualizations simplify complex data for users, they can make decisions quickly. Take a look at Intralinks’ charts, for instance. They show the trend and predictions for equity investors across different regions and that helps them quickly decide where to invest. 

Intralinks, though, is just one of many examples. Let’s see some others so you see how important interactive visualizations can be.

What are some examples of interactive data visualizations?

Interactive visuals are being used across different industries to simplify data and help people uncover insights from otherwise complex data. 

Here are some examples of data visualizations to inspire you:

1. Ahrefs’s performance chart

Source: Ahrefs

Ahrefs, the popular SEO tool, has a performance chart that’s a good example of this interactive data visualization we’ve been talking about.

This graph plots different metrics against each other such as referring domains or organic traffic against a timeline. And overall, it helps people monitor their site’s performance in the SEO world. 

What makes it an interactive visualization is that users can interact with data by hovering over points to reveal their site’s referring domains or organic traffic the site has attracted. The chart also has filters such as duration, location, etc. to refine its data so users can fully explore their SEO performance trends.

2. COVID-19 retail pulse report

These interactive graphs by Wunderkind, a global performance marketing solution, visually depict the changes in web visits, conversion, interactions, and revenue that e-commerce marketers experienced during the pandemic. 

Here, hovering over the graph lines is how users interact with the data. Doing that displays the percentage changes in different performance metrics so it’s easy to understand. So when users hover over a point, for example, a note box appears showing the conversion rate for a particular day.   

3. Construction market trends

This data visualization shows how much building properties costs over four years. Hovering over graph lines is how interactivity is leveraged here, making it easy for people to understand the data and pick important information.  

To the right side is additional information about materials used in construction that users can click on to get more details. Going further through the document is a map showing construction price forecasts across different locations. Users click on a location and it shows the forecast for that region, simplifying complex data for viewers.

While this is pretty exciting to see, we know 🙃, let’s discuss techniques used in interactive data visualizations.

What are some key interactive data visualization techniques?

Since we’re dealing with data, this section will cover common interaction techniques used in telling better data stories, to help users with their exploration. 

Here are some of them:

• Number counters: A flash of numbers counting downward helps condense a buttload of data into a countdown and creates a sense of excitement or expectation in viewers. 
• Animated charts: This covers line graphs, bar charts, pie charts, and even infographics but not as you know them. This version features animated elements that capture people’s attention and encourage them to engage with the data. Here’s an example from Adecco:

See how when you hover over it, the lines change colors and numbers appear? That’s a great way to catch people’s attention and keep them focused.

• Show/hide: Using this technique involves hiding some bits of information like numbers, text, or even visuals and revealing them when the cursor hovers over them. This makes readers curious about what else the data report is hiding and they’ll want to see more. 
• Scroll-triggered animations: Visual animations that come alive when users scroll are another way to make your data stand out. Sky News used this technique briefly when they were telling a brief Brexit history in their Brexit-by-numbers story.

GIF Source: Sky News

As users scroll through, the information they see changes, keeping users informed without using overwhelming data. 

• Scaling: Scaling is used to change the aspect ratio of the graph or map so users can zoom in or out of the content.  

Next, let’s chat about tools that can help you create these interactive data visualizations.

What are some key interactive data visualization tools?

Thinking you might need data stories for your business? The traditional route involves hiring researchers to dig up the data and then relying on a team of designers and visual artists to bring it all to life.

But why not streamline the process? Interactive data visualization tools empower you to create engaging representations of data yourself. With features like filtering, clicking, and hovering, these tools allow users to explore and interpret data in a dynamic way.

Here are some of them:

• Ceros: A no-code content creation platform, Ceros allows you to create interactive data visualizations using Studio. It has several templates in the database to pick from and start editing. You can add animations, clickable elements, and hover effects users can interact with for a more engaging experience. 
• Thoughtspot: This AI-powered analytics platform enables users to create personalized insights from your cloud data. You specify the data you’d like to visualize and it automatically creates the interactive content.
• Google Charts: Yup, Google has a foothold in data visualization through Google Charts. This JavaScript-based tool lets you create interactive visualizations for small and large datasets on your website with pre-programmed codes.

Now, other tools can help you visualize data. They include specific Python libraries such as Matplotlib, Bokeh, PyGWalker, and leaflets from the famous statistical programming language, R package.

Here are some other popular options data scientists use:

• RAWGraphs, an open-source data visualization tool.
• Plotly, supports using artificial intelligence for creating data stories.
• Datawrapper, ideal for journalists to transform datasets into visualizations optimized for web and mobile experiences. 
• Power BI, a tool for businesses, allowing them to import their data, analyze it, and present it using interactive visualizations.
• Qlik, a tool for large enterprises that want to showcase their data by employing augmented analytics.

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Right, we think you’re ready to learn how to create data visualizations. Find out in the next section.

How can you create interactive data visualizations?

If you’ve decided to create data visualizations, here are four steps to set you on the right track. 

• Data collection and analysis: The first thing to do is gather your data. Obviously! 🙄 If you’ve got a team of researchers, this is when to hit them up to send their work or import the data from survey tools, etc. 

Then, transform it into ready information people can understand. This is where your data analyst team shines or you use Microsoft Excel or Power BI to refine the data. 

• Identify your goals: At this point, you need to think about what you’re trying to achieve. Why do you want to create interactive data visualizations? 

Defining this helps guide what design approach you choose, prioritize which data should go on the chart to avoid information overload, and provide benchmarks to evaluate the success of the visuals. To identify goals here, a good way to go is to discuss them with your team. 

In most cases, the objective will probably be to educate the audience or provide them with information to make crucial decisions.

• Select the visualization design: Based on the goals you’ve just defined, it’s time to decide how the design will look. You need to look at charts, graphs, or maps to help achieve your goals. And more importantly, make it easy for users to work with the data. 

Here are some tips to help you choose a data visualization format:

• If there’s a comparison involved in your goal, using bar charts is advised. 
• Showing trends over time? Line charts are the way to go. 
• Is there distribution involved? Holograms or pie charts are good options.
• Use scatter plots to show relationships between data. 

• Allow collaboration: Want to ensure the interactive data visuals are meeting your goals? Collaborating with stakeholders and teammates will help make that happen. Allow them to explore and share their feedback so you can refine the visualization to meet your target audience’s needs.  

If you're diving into Studio—because why wouldn't you?—here’s how to create interactive data visualizations:

• Log into Ceros and create a new project by selecting a new canvas or a template that meets your data needs.
• Import static graphs or charts from external tools. 
• Add interactivity by applying hover states, clickable actions, or animations to elements like the bars or lines in the chart. 
• Throw in animations with Ceros’s animation features where the bar chart assembles, for instance, when the page loads or the user scrolls.

• Invite teammates and stakeholders to collaborate and share their input using MarkUp.

Generally, when creating an interactive data visualization, you need to ensure: 

• It’s shareable and can be engaged across multiple devices, e.g., smartphones and PCs. 
• It’s simple. We get that you‘d like to wow people. While that’s great, making it easy to understand is the way to go as it’ll encourage users to continue exploring for more information. 
• It’s intuitive. Viewers should be able to interact with the data without a user manual. Of course, if it’s complex data, having a legend can help provide context when interacting with the graph. 

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All this talk about interactive data visualization… what about the static version?

Is it not a great option to use or how does it differ? 

We’ll talk about that in the next section.

How does interactive data visualization differ from static data visualization?

Static data visualization doesn’t have any interactive or engaging features as its counterpart does. It focuses on telling data stories from a single viewpoint. 

It’s a good option for conveying simple, straightforward information. 

Interactive data visualization, as we’ve explained, is a visual data representation where users can interact and explore data points. It helps give them more insights into complex issues.

With that cleared up, we can officially bring this piece to a close. But there’s one more thing to note below before we say goodbye.

Tell your data story with Ceros

Ready to kick off your interactive data visualization journey? 

Look no further than Ceros! It lets you transform static charts into engaging interactive graphics that users can’t wait to explore—no technical skills needed. With user-friendly features and pre-made templates, getting started is easy!

Check it out yourself by scheduling a free demo.