Business dashboard design: The fundamentals of data visualization
Your team and you have been working hard to map out your company’s key performance indicators. You’ve written down your key business questions, gathered all the raw data that matters, and are ready to build a dashboard that integrates seamlessly into your day-to-day work. Now what?
We understand that the hardest part of building a dashboard report is cleaning up that data and matching it to the right visualization. Data visualizations turn your raw numbers into visual graphs that identify key relationships, trends, and patterns. Essentially, these visualizations bring your data story to life and are at the heart of every successful business dashboard report.
Matching data to the right visualization begins by answering these three key questions:
- What relationship am I trying to understand between my data sets?
- Am I looking to compare multiple values or looking to analyze a single value over time?
- Is this visualization an important part of my dashboard’s overarching data story?
With those questions (and hopefully, answers) in mind, we’ll dive into the 8 most common data visualizations you can mix and match to build your dream dashboard. We’ll provide you with best practices and real-life business examples, so feel free to navigate to the one you want to explore the most.
1. Bar charts
It seems like at some point or another, everyone has either seen, interacted with, or built a bar chart before. Bar charts are such a popular visualization because most people are familiar with how to quickly scan them. They organize data into rectangular bars that make it easy to compare related data sets.
Above, you’ll find an example of how we use a bar chart with Google AdWords data to measure ad cost over time. Understanding the relationship between our previous period’s and current period’s ad cost is crucial for our day-to-day marketing decisions.
When do I use a bar chart visualization?
Use a bar chart for the following reasons:
- You want to compare two or more values in the same category
- You want to understand how multiple similar data sets relate to each other
Don’t use a bar chart for the following reasons:
- The category you’re visualizing only has one value associated with it
- You want to visualize continuous data
Best practices for a bar chart visualization
If you use a bar chart, here are the key design best practices:
- Use consistent colours and labeling throughout so that you can identify relationships more easily
- Simplify the length of the y-axis labels and don’t forget to start from 0 so you can keep your data in order
Maps are an amazing visualization to add to your dashboard if organizing data geographically tells an important story for your business. For example, if your dashboard is looking looking at monthly sales, it could be extremely useful to see the geographic locations of your customers.
Above, you’ll find a map visualization that integrates with Salesforce to measure accounts by country. Keep in mind that if your dashboard is looking at daily sales, this visualization may provide less value to your day-to-day discussions.
When do I use a map visualization?
Use a map for the following reason:
- Geography is an important part of your data story
Don’t use a map for the following reasons:
- You want to show precise data points
- Geography is not an important element of the dashboard’s overarching story
Best practices for a map visualization
If you use a map visualization, here are the key design best practices:
- Avoid using multiple colours and patterns on your map. Use varying shades of the same colour instead
- Make sure to include a legend with your map, so that everyone understands what the data means
3. Line charts
Let’s face it; line charts are amazing. Line charts visualize data in a compact and precise format which makes it easy for users to rapidly scan information to understand trends. The best part is you get to use colours to tell a story! The proper use of color in this visualization is necessary because different colored lines can make it even easier for users to analyze information.
At Klipfolio, we think line charts and Facebook Ads data go hand-in-hand. You can use line charts to drill down on most comparisons! Above is an example of how using a line chart can tell the story of your cost per impressions and cost per 1000 people reached over a certain period of time.
When do I use a line chart visualization?
Use a line chart for the following reasons:
- You want to understand trends, patterns, and fluctuations in your data
- You want to compare different yet related data sets with multiple series
Don’t use a line chart for the following reason:
- You want to demonstrate an in-depth view of your data
Best practices for a line chart visualization
If you use a line chart, here are the key design best practices:
- Along with using a different colour for each category you’re comparing, make sure you also use solid lines to keep the line chart clear and concise
- To avoid confusion, try not to compare more than 4 categories in one line chart
Scatterplots are typically not the clearest way to scan information, so if the visualized data is being shown on a TV dashboard, it will be difficult to quickly understand the displayed quantitative measures. This data visualization can be most useful when quantitative measures are frequently changing and a user's day-to-day monitoring would benefit from seeing those changes.
When do I use a scatter plot visualization?
Use a scatterplot for the following reasons:
- You want to build an interactive report
- You want compact data visualization
Don’t use a scatterplot for the following reasons:
- You want to rapidly scan information
- You want clear and precise data points
Best practices for a scatter plot visualization
If you use a scatterplot, here are the key design best practices:
- Although trend lines are a great way to analyze the data on a scatterplot, ensure you stick to 1 or 2 trend lines to avoid confusion
- Don’t forget to start at 0 for the y-axis
Does your business dashboard measure many metrics? Do you want to understand the trends between all these metrics? Say no more! Sparklines are arguably the best data visualization for showing trends on a business dashboard because of how compact they are. They get the job (of analyzing data) done quickly. It’s important to make sure your audience understands how to read sparklines correctly to optimize their use.
We use sparklines every single day at Klipfolio, especially to track website performance. Above you’ll find many sparkline visualizations that come together to tell the story of our Google Analytics data. Adding the percentages on the side bar is a best practice we like to follow to assist in the readability of the data.
When do I use a sparkline visualization?
Use a sparkline for the following reasons:
- You can pair it with a metric that has a current status value tracked over a specific time period
- You want to show a specific trend behind a metric
Don’t use a sparkline for the following reasons:
- You want to plot multiple series
- You want to illustrate precise data points (i.e. individual values)
Best practices for a sparkline visualization
If you use a sparkline, here are the key design best practices:
- To assist with readability, consider adding indicators on the side that give a better glimpse into the data, like in the example above
- Stick to one colour for your sparklines to keep them consistent on your dashboard
6. Pie charts
Everyone has a love-hate relationship with pie charts. At a high-level, they're easy to read and understand because the parts-of-a-whole relationship is made very obvious. But top data visualization experts agree that one of their disadvantages is that the percentage of each section isn’t obvious without adding numerical values to the visualizations.
So, what’s the point? As long as you avoid common pitfalls and stick to best practices, pie charts can be a quick way to scan information. One of the easiest ways to use pie charts is with Google Analytics data. Just like we can see above, a pie chart quickly tells us our sessions by device type; however, being the data nerds that we are here at Klipfolio, we like having the numbers beside the pie chart to tell us exactly what we need to know.
When do I use a pie chart visualization?
Use a pie chart for the following reasons:
- You want to compare relative values
- You want to rapidly scan metrics
Don’t use a pie chart for the following reason:
- You want to precisely compare data
Best practices for a pie chart visualization
If you use a pie chart, here are the key design best practices:
- Make sure that the pie slices add up to 100%. To make this easier, add the numerical values and percentages to your pie chart
- Use a pie chart if you have only up to 5 categories to compare. If you have too many categories, you won’t be able to differentiate between the slices
Gauges are different from the other data visualizations we’ve just explored because they typically only compare two values on a scale: they compare a current value and a target value, which often indicates whether your progress is either good or bad.
I love using gauges to measure how much time I spend in meetings weekly, by connecting to my Google Calendar data. Just like you can see above, this data visualization helps me gauge (pun intended) whether I’m spending too much time in the boardrooms as opposed to checking off my to-do list.
When do I use a gauge visualization?
Use a gauge for the following reason:
- You want to track single metrics that have a clear, in the moment objective
Don’t use a gauge for the following reasons:
- You want to track multiple metrics
- You’re looking to visualize precise data points
Best practices for a gauge visualization
If you use a gauge, here are the key design best practices:
- Feel free to play around with the size and shape of the gauge. Whether it’s an arc, a circle or a line, it’ll get the same job done
- Keep the colours consistent with what means “good” or “bad” for you and your numbers
If you’re someone who wants a little bit of everything in front of you in order to make thorough decisions, then tables are the visualization to go with. Tables are great because you can display both data points and graphics, such as bullet charts, icons, and sparklines. This visualization type also organizes your data into columns and rows, which is great for reporting.
Above is an example of how to bring in your Google Analytics data into a table, so that you can see all the information you need in one place.
One thing to keep in mind is that tables can sometimes be overwhelming if you have a dashboard with many metrics that you want to display. It's important to find a happy medium between large amounts of data (confusing) and too little data (waste of dashboard space).
When do I use a table visualization?
Use a table for the following reasons:
- You want to display two-dimensional data sets that can be organized categorically
- You can drill-down to break up large data sets with a natural drill-down path
Don’t use a table for the following reason:
- You want to display large amounts of data
Best practices for a table visualization
If you use a table, here are the key design best practices:
- Be mindful of the order of the data. Make sure that labels, categories and numbers come first then move on to the graphics
- Try not to have more than 10 different rows in your table to avoid clutter
Final thoughts on data visualizations for dashboard design
There are countless data visualizations out there and they all tell different yet impactful data stories. In other words, your data isn’t rendered visually useless just because it doesn’t work in one particular form of data visualization. You just need to help your data find its visual match. Once you've got that covered, you can start pinpointing key insights and trends.
Some honorable mentions of data visualizations that we didn’t dive into today are area graph, donut chart, funnel chart, spark bar, bubble char, and pictograph. The list really goes on! When put together on a single dashboard, these visualizations make magic.
It’s also important to mention that data visualizations aren’t limited to certain colors, icons, and overall design. You’re the artist here; your visual preferences can make a difference when telling your story (play around with the dashboard below to see what we mean):
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Originally published December 10, 2018, updated Jun, 13 2019