Category: Data Visualization

While visualizing data, all of us know about the pie chart or the line graph. These graphs are some of the most common and basic visualizations of data. However, these graphs are only the tip of the iceberg. There is a whole range of visualization methods that can be used to present data in the most effective manner.

Though the nearly endless possibilities lead to another issue, which one do you choose?

Exploring Some Common Visualizations

In this post, we will discuss some of the most common data visualizations and more specifically when they communicate your data clearly and when they don’t. Again, there are wide choices available, so we can’t cover them all, but the ideas presented can be applied to any visualization you come across in the future.

Line Chart

If there was an “old reliable” of the data visualization world, the line chart would be it. However, despite the old part being true, the reliable part should probably be up for debate. Line charts show one thing very well and that is numerical data combined with an ordinal attribute. 

For example, transaction totals over time. That is due to the structure of the purpose of the line chart. At the end of the day, what the line chart is designed to show is how something moves from one ordinal data point to another. 

In cases where the data shouldn’t be connected in such a manner, all a line chart does is confuse the viewer. A line chart should only be used to communicate a maximum of 3-5 “lines” at a time, any more than this and the chart begins to feel crowded and look confusing. 

The two biggest offenders for bad line charts are too many variables (as seen to the right) or too high a frequency. Both of these mistakes cause a line chart to be confusing and hard to understand.

Gauge Visualization

The needle gauge is an incredibly popular visual and has some strong benefits. 

We’ve been conditioned since we learned to drive to trust and love gauges. They are very efficient at showing a single numerical data value at a single point in time. People love their simplicity, but that’s also their weakness. 

A gauge is an exceptionally clear visual. It shows exactly where a number falls between a minimum value and maximum value. If you want to show how your sales performance was for a specific time period, a gauge will allow a user to instantly know if you did better or worse than expected.

However, this simplicity is also an issue for gauges and similar one-dimensional visualizations. It can only be used to show a single number, and it takes up a lot of room. That’s fine in a car dashboard, where you only care about a few key real-time metrics like speed, RPM, and engine temp. But on a business data dashboard, prime real estate is valuable. It is for that reason we like to use gauges sparingly.

Choropleth Map

A choropleth, also known as a filled map, uses differences in shading or coloring within predefined areas to indicate the values or categories in those areas.

This is useful when you want to see what states you have the most sales in for example. These sorts of maps are very good at showing such distributions. However, they don’t have the granularity of other visualizations.

Table

Yes, sometimes a simple table is the best way to show data. However, if a table is going to be used as part of a dashboard, it needs to be used properly. This means things like conditional formatting or in-depth filtering must be applied. 

The goal of a table in a dashboard should be just like the rest of these visualizations, to show something specific! It should be highlighting something like customers who have an outstanding balance. Do not fall into the trap of just showing the data again, otherwise, why did you spend time and money on visualizing your data at all?

There are some important rules to follow when making dashboards and to ensure your dashboard hits the mark it needs to and gets people using it. Now let’s dive deeper into what makes a good dashboard.

1. Make sure you are designing the right dashboard for who is going to be using it

If you are going to spend your time and energy making a good dashboard you need to know who the dashboard has to be “good” for. Executives will want to see something different from a salesperson and so on for a data analyst, you need to know about the audience of the dashboard. The most effective dashboards are those which target a single user or group of users and then provide the right data and visualizations accordingly. A lot of people overlook this step, which creates havoc later on.

2. Display the dashboard data in a logical manner

Ensure that your data is displayed in logical groups, and in a proper manner. The top left-hand corner of your dashboard is where the eye will immediately go to and as such, it is the most important part of the dashboard. When we say to display the data in logical groups that is to say; if you are making an executive overview that compares two marketing strategies, the data for each strategy should be grouped together so that all of the visualizations for strategy A go on the left and all of the visualizations for strategy B go on the right.

3. Vary your visuals

When it comes to dashboards, variety is always better. Don’t use only one chart type, no matter how much you love stacked bars. Mix it up with straight lines and curves. Vary your report elements between low-level tables that show granular data and higher-level pie charts, gauges, and value widgets.

Here is an example of a good variety of visualizations for a monthly recap. It immediately shows the important totals as well as a comparison to last month and where our customers are coming from.

4. Locate the most important visuals “above the fold”

Above the fold is an old newspaper term, and it means the top part of the front page, which is still visible when the paper is folded. For dashboards, this means the screen real estate at the top is visible when the dashboard is first loaded by the user. Put your most important and/or summary level visuals at the top. Tools like Inzata (https://qastaging.wpengine.com) let you view heatmaps of how your users scroll and navigate within their dashboards. Use these to identify their most important and most-viewed elements and move them near the top.

5. Don’t forget your headline

You’re probably tired of all the newspaper references, but hey, there’s a reason why nearly every print newspaper on Earth is organized in more or less the same way: it’s effective.

What do headlines do? They communicate the main message to the reader about what happened or is happening. They’re in big, bold print so they’re hard to miss. We recommend using a nice row at the top consisting of 3 or 4 easy-to-spot widgets that are easy to read, like gauges or single-value widgets. This “headline” row quickly delivers key information to the viewer and sets the stage for further exploration as they continue reading.

6. Always refresh your data

Data that is being displayed on your dashboard only maintains importance if it is up to date. If you are trying to decide what to do tomorrow based on data from three months ago, you are going to arrive at the wrong conclusions.

7. Keep your dashboards focused!

Make sure that the most important data gets highlighted in the dashboard. You should also keep your dashboard small so that it is able to focus on the thing which is most important. Long dashboards aren’t always the best. Many small dashboards, which are focused on a single topic or goal, make a better dashboard than long and heavy ones.

Your dashboard should be focused on answering a single question and should almost never have more than five or six visualizations. It may be tempting to make one huge dashboard where someone could find all the answers, but that is not how people’s brains typically work. It will result in users feeling lost and confused because they can’t find what they need quickly. If it takes someone more than 5 seconds to find what they need on your dashboard, consider redesigning it.

What is Data Storytelling?

How do you tell a GREAT story with data? 

Everyone likes hearing a good story. However, being asked to “tell a story” using data and visualization is often a big source of anxiety for analysts of all backgrounds.

An informal Twitter poll returned the following responses to the question “When I’m asked to show the data, I feel….”

Frustrated, because I don’t think I’ll tell the story effectively, and might miss important parts.

I feel pressure, pressured to make it clear for everyone, and what if people don’t like my story?

Inadequate, because I’m sure there are questions people will have that I haven’t anticipated.

Being able to tell stories with data is a skill that’s becoming ever more important in our world of increasing data and the desire for data‐driven decision-making. As more and more data visualizations are produced, they start to become a commodity and their quality suffers. This turns off viewers and people begin to rethink their investments. However, great Visual Storytelling can send the effectiveness and reach of your analysis through the roof and produce significant business influence, value, and career rewards.

Have a look at the graphic below. What story do you get from it? 

Here’s what most people see:

1. The average surface temperature is trending higher.
2. Multiple independent data sources all show the same trend, which lends further credibility.
3. Temps were trending lower at one point, but that reversed and has started growing in lockstep with the rise of industrialization.

Even though it’s little more than a few words, numbers, and some colored lines, it tells a very compelling story, with strong supporting evidence, and makes its key points very persuasive.

Storytelling with data is no different than regular storytelling. Storytelling is by far the longest-running and most effective method of human-to-human knowledge transfer. The reason storytelling is so effective is that it engages emotions along with cognition (ability to learn). Emotion keeps you interested while you learn. 

• Build Characters: First and foremost, stories involve characters. Without humanized characters, there’s nothing for the viewer to relate to; It’s not a story. Think about it. Every story you’ve ever read has human-like characters for you to relate to. Even movies and stories about animals and inanimate objects impart human characteristics to those characters: they talk, they react, they have expressions and emotions, they act human. In data, the character(s) can be you, or the reader, or named people, or people in a certain role, customers, employees. e.g. “Our Sales managers wanted to know how to ….” “I sought to uncover why ….” “Our CEO, Mike, asked me to investigate why ….” or even, “My daughter asked me about our company, and she wondered why X product was so successful….” A great way to introduce characters visually is with earlier Survey Results. The survey results let you introduce and describe characters, “Male employees, under 40, working in our US Offices had the following to say in a recent survey:” and also give them a voice.
• “Use the Force, Luke”. The next thing that is required is some kind of goal, challenge, or objective. This line from Star Wars was Obi-Wan’s way of challenging Luke to learn the Jedi way and set out his hero’s journey. The characters must want or need to do something. That’s the hook. That’s what gets the reader to go along with the character, to put themselves in their shoes. In data, a great one here is answering a difficult question or solving a business problem. Even better would be showing how your insights and answers resulted in a measurable improvement. So give your characters a challenge to overcome. The bigger the challenge, the more interesting the story becomes because….. 
• ….“Never Tell Me The Odds”: Give the character some stakes, some consequences of complete failure. Optional: Let the character fail, but use it to illustrate what they learned. Failure makes the stakes seem real and pulls the reader in even further. This is called “rising action”. Just don’t lay it on too thick.
• “Have a Point!“: Every story needs a climax, a point where the action peaks. This should involve being the main message you’re trying to communicate. It should always involve your character(s) achieving or exceeding their goal. For example, if your “challenge” was to use analysis in order to create a plan to change something, you can include a Gantt chart or Change Roadmap here as the deliverable of that analytics journey. You could also phase shift this slightly to show a visualization of what the Outcome of that Change was.
• “Falling Action.” Now that you’ve made your main point, you can use this part to tie up loose ends, resolve other challenges or conflicts besides the main one, describe what happened to the characters after the story, or even use it to tease a sequel. You can also use this part as a “Call to Action” for the viewer if you want them to do something, such as give feedback or share your dashboard with others. 

Now that you have the main foundations of Data Storytelling under your belt, give it a try. The best way to master it is to practice it often. Learn what works best for your data and your audience. A-B test different approaches and get feedback on what worked. Look back over earlier work from yourself and others and list out the things you might have done differently now that you have this new knowledge. Hopefully having a structure like this to start with will give you confidence in choosing and arranging your next visual exercise to maximize its message and persuasiveness. How will you know you’ve succeeded? People will tell you. People know good storytelling when they experience it. Good luck!

In the digital economy, data is mana. It’s the fuel that keeps the tech and marketing sectors churning. But when using data as a sales or education tool, plain old stats and facts just aren’t enough. Massaging data into a compelling story is key to onboarding clients, securing investors, and training employees.

Human brains are wired for stories. As evidence, a Stanford Business School study revealed that 62% of participants remembered stories while only five percent remembered straight statistics. That’s an immense difference, and the results should have every business asking: How can we transform our data into engaging narratives that sell, convince, and teach?

What is Data Storytelling?

Without framing, data can come across as flat, bland, and vulnerable to interpretation. Businesses wanting to burnish their brands in the brains of target audiences must carefully craft their messaging and bolster it with supporting data.

Why is Storytelling So Effective?

Storytelling is how cave people evolved into modern individuals. It’s a linguistic tradition hard coded into our DNA; it’s how civilizations passed down survival skills and traditions. Storytelling remains an integral part of how we process and retain information.

Read more: Data Storytelling: The Essential Skill for the Future of Analytics

What is the Goal of Storytelling?

The goal of data storytelling is to engage audiences. You can highlight insights that will stick, convince, and stimulate the desired action by packaging narratives in digestible and engaging bites of information.

As a presenter, your job is to focus people’s attention on the most salient and engaging points. Think of yourself as the Degas of data — someone who paints beautiful pictures using stats and trends. By framing the mundane in gilded casings, you’re heightening the audience’s emotional response, which leads to better retention of the material.

Three Steps of Effective Data Storytelling

We’ve discussed why data storytelling works. Now let’s dig into the “how” of the matter.

Become Intimate With the Data

Before crafting data stories, familiarize yourself with the information. Don’t manipulate the data to suit your needs. People instinctively pick up on phony or inflated stats — and that diminishes trust. Instead, become intimate with the facts and figures and find the actual statistical trends hidden within. They’re more impactful than jerry-rigged half-truths.

Understand Your Audience

The next step is getting to know your audience. What makes them tick? What do they care about? What’s their worldview? How does your data connect to their goals? The answers to these questions will shape a story that connects with your targets emotionally. Once you tap into their zeitgeists, you can more readily sell the vision.

Remember that one size does not fit all when it comes to data narratives. The tale you tell to a room full of mid-level managers will differ from the one you tell executives.

Choosing the Right Data and Presentation Style

Visuals matter — a lot. They help clarify, connect, compare, and provide context. Effective visualizations include information about the most compelling data as well as highlight the best parts. While it’s almost always better to have professionals design presentations, here are a few DIY pointers:

• Comparisons: If you want to highlight comparisons, use bar, line, and circular charts.
• Composition Statistics: Showing data composition statistics is best done with pie charts.
• Distribution of Data: Line distribution charts work for displaying data distribution points and trends.
• KISS: When creating charts and graphs, adhere to the adage “keep it simple, silly.” Leave the 3D renderings and drop shadows to game developers. They only mess up business presentation aesthetics and may come across as outdated.
• Color Consciousness: Data presentations are not the time to express your inner Rainbow Brite! Choose a pleasant color palette and use complementary colors; they’re easier to understand at a glance than a hodge-podge of hues.
• Language: Use words and phrases that your audience understands. Don’t try to “sound smart.” It never works and can reflect a lack of confidence and communication.
• Layout: Each slide should have a call to action, a header, and a short narrative summary. People’s attention wanders during presentations. Combat this by keeping things clear and concise!

Crafting effective data narratives that speak to people’s desires and emotions is a skill that takes time to develop. Professionals understand how to mold micro and macro elements into engaging stories. It’s no question that data storytelling is an invaluable tool. And when done correctly, profits follow.

1. Develop a Plan

It’s natural to want to play around with your data and jump right into building dashboards. Nevertheless, when beginning, try not to start creating and adding charts right off the bat. It’s useful to plan ahead and layout the details of your dashboard prior to actually constructing it. This means determining the overarching purpose of your dashboard as well as what information needs to be included. Planning ahead will help to minimize overcrowding and continual adjustments to your design later on. 

What Should Go Where?

Thinking about the user’s experience when viewing a dashboard is essential when it comes to deciding where specific information should go. Here are a few things to think about when determining your initial dashboard design plan.

Placement

There is only one thing to be said about placement: location, location, location. While your dashboard is far from the real estate sector, consider that users will naturally give more attention to the left side of the screen. According to a recent eye-tracking study, users spend 80% of their time viewing the left side of the screen and only 20% viewing the right. 

Specifically, users were found to look to the top left corner of the screen the most, making this section of your dashboard prone to increased amounts of attention. The most utilized graphs and metrics should be placed in this portion of your dashboard, or any additional visualizations you deem significant. 

Don’t Hide Things

Similar to the point above regarding placement, you want to prioritize key information and make sure it’s easily found. You can’t expect much work from your end viewer to dive deeper than the surface data presented. Any additional clicking or scrolling required to find information is unlikely to be discovered by viewers. 

All things considered, an easy way to solidify your plan would be to create a rough draft either on paper or in any design application. This will allow you to play around with your placement and take a deeper dive into how certain elements complement each other.

2. Sometimes Less is More

We’ve all heard the common phrase that sometimes “less is more,” and dashboard design is no exception to this philosophy. You want your dashboard to be clear, concise, and easy to read. Avoid including too many charts and any unnecessary information. While an abundance of charts and graphs might appeal to the data driven enthusiast in you, they might be difficult for other viewers to read and understand. Minimizing the amount of data presented will prevent your audience from feeling overwhelmed due to information overload.

Choosing the Right Data Visualization

Choosing the most effective visualization for your data plays a key role in your dashboard’s simplicity. This is dependent on the type of data you are trying to visualize. Are you working with percentages? Data over a specific period of time? Are there any relationships present that you are trying to convey? 

The many variables that make up your data will affect your ultimate choice in visualization. Be sure to consider characteristics such as time, dates, hierarchies, and so on. 

3. Keep the End Viewer in Mind

Your audience is just as critical to your dashboard’s design as the information being presented. It’s important to always keep the end viewer in mind and understand how they are actually using the presented information.

When determining the characteristics of your end viewer, ask yourself questions such as:

• Who will be viewing this dashboard on a daily basis?
• How often do my viewers work with the type of data being presented? 
• How will my audience be viewing this dashboard? Will viewers be sharing it as a pdf?

The answers to these questions will help you determine how much descriptive information to include alongside your visualizations.

Overall, there are numerous elements to consider when it comes to developing your business dashboards. It’s vital to always keep your audience in mind and plan ahead. Consider these key tips next time you’re building a new dashboard for improved design.