KEY PRINCIPLES OF GOOD DATA VISUALIZATION
As we are currently in a data-driven world, the ability to be able to effectively transmit data that an audience will be able to easily understand is essential. This has made data visualization very important to convey information to your audience – internal or external.
Over the years, it has been noted that humans tend to remember pictorial representations of things than words. Data visualization can be done in different formats so far it is representing data in a visual form. These formats include; a graph, chart, image, etc.
Ultimately, the role of data visualization is to communicate the difficult and hidden aspects of a data. Although, a data analyst or scientist may have the ability to see the key insights in a complex collection of unorganized data because he/ she has been trained to do so, an average human will not be able to do the same.
And this is why effective data visualization is a very necessary and important thing. Effectively communication of data is an art that most data scientists or analysts cannot do.
What is Data Visualization?
Data visualization is the graphic representation of data.
Data visualization simply means the drawing of graphics display to represent data. It is all about representing complex data in a graphical format It is a way through which information can be made more understandable.
The aim and objective of data visualization are to communicate information clearly and efficiently using graphical means.
Data visualization is used in data cleaning, identification of trends and clusters, detecting local patterns, spotting outliers and unusual groups, evaluating output, and presenting results.
What are the Key Principles of Good Data Visualization?
To effectively represent a data and pass information across through the process of data visualization, it is important to put some things into consideration as there are principles governing data visualization.
These principles that guide data visualization help to efficiently pass the intended message to the audience.
By effectively applying these principles, there will be an improvement in the way you display, analyze and process data. In this article, we will discuss in detail the key principles of good and effective data visualization.
1. Determine the appropriate visual
The first thing to do in data visualization is to understand how much data is at hand and identify which format of data visualization will best fit and – more importantly – convey your message appropriately.
You need to make sure you are representing the data well and in a way easy to digest way.
There is a whole debate between operations and analysts over the use of a pie chart. When to use one depends on what you are trying to show and how many categories are represented. Showing a part of a whole. Yup. Showing how 10 categories make up the whole is just not the best way to compare the categories.
Debate solved. In my head at least!
There are a lot of different chart types. The choice as to which one to use matters!
2. Determine your target audience
It is also important to know who will be receiving or going through your end state reporting. This is to enable you to use a format of data visualization that they can easily comprehend.
No matter the level of data visualization it will still be useless if it is not designed in a way that will make the target audience understand and comprehend it.
It also helps you to meet their expectations. I see way too many request for a dashboard to be created that basically resembles an Excel spreadsheet. They just want something automated & published.
Knowing your target audience will help you craft an end result that will actually help them garner valuable insights.
In these instances, I like to give them what they ask for but also provide a graph or full-on dashboard that SHOWS gaps. That said, if you throw some bubble charts and complex visualizations at this person, they’re not interested.
Knowing who will consume your data lets you understand where they are at in their data literacy journey and how to make the most of your time… and theirs!
3. Grab your audience’s attention with the visuals
As a visual tool, data visualization is about making use of visual elements such as; charts, graphs, pictures, maps, etc. to successfully get the attention of your audience, you need to put some things into consideration while making a design that will grab your audience’s attention.
Balance your design
To make your design balanced, you need to ensure that all visual elements such as the color, shapes, texture, negative spaces, etc. are evenly distributed in the design. There are 3 types of balances in design.
- The symmetrical balance- in this balance, each side of the design is the same.
- Asymmetrical balance- in this balance, both sides of the design are different although they still have similar visual weight
- Radial balance- in this balance, elements are randomly places around a central object. This object acts as an anchor to the other elements.
Balanced design falls under a graphic design kind of framework, so while you can use your gut, you would definitely benefit by researching additional principles of design to level your data visualizations up.
Lay emphasis on the important areas
The aim of data visualization is to ensure that the most important part of the data does not go unnoticed. The design should be done in a way that the audience’s attention is drawn to the most important data on the design.
This can be done through the layout, color, and size primarily.
Most users will consume data from the top left moving to the right AND THEN down. Whatever you want front & center gets that top left real estate.
Use color appropriately. Red, amber, and green reports are AWFUL. They are an assault to the eyes. If you don’t agree, let’s walk through this. Aren’t you really targeting the red anyhow? Once the red is handled, you want to handle the yellow? How often do you even get to the yellow?
Even if this is important to you, you can use the visualization software to highlight what is important to you that day.
If you’re still not won over, then let me tell you that 1 in 8 men have some form of color-blindness. Red, yellow, green reports can’t be fully seen easily by them to make the same actionable insights another stakeholder can see.
Make use of patterns – sparingly
Patterns make is a great way of showing similar types of information that are spread across a page as one. A pattern can also help to point out an abnormality as a disturbance in the pattern will naturally draw the attention and curiosity of the audience.
Patterns go beyond the idea of some lines across a bar in an Excel bar charts.
Variety
Variety is a key factor in grabbing your audience’s attention and making them engaged and interested in your data. Variety is all about finding different ways to visualize your data by using various interesting design elements.
However, don’t throw out the bullet around considering the type of chart that BEST FITS THE DATA AND STORY.
Hello ridiculous versions of charts for the sake of variety. I’m looking at you! I recently had a request to compare 1 metric to a historical version of that same metric or a forecast. Over and over.
I won them over by repeated use of a single bar with a line to represent the comparison. I added color to understand the variance & decide which bar to care about, but ultimately, there are a lot of bars. And that was a happy client.
Theme
A theme helps you to make sure that your design follows a particular standard. A theme helps you to connect with your audience on a deep level and it also increases the visual design.
Themes can also be considered a type of branding. Branding a department. Branding by a report type. You can get creative with what this looks like for your organization.
I have had many instances where I was taking the framework of someone else’s dashboard & using it in a new way. If the request and audience allows, I like to keep elements such as title style or filters as similar as possible. Doing this allows users of both dashboards to dive in with an existing comfort level.
Plus there is no sense reinventing the wheel. Take the wins where you can!
Make it simple
Make sure that your visual is easy to understand and simple. Endeavor not to use unwanted and irrelevant information as this may make your visual confusing which will not help in achieving the aim and objective of the data visualization.
Always have in mind that simplicity is the final goal of data visualization.
Have you heard of the term ‘white space’? Sometimes, less is more. If you are looking at a wall of information, clearing some of it out helps highlight elements.
It’s crazy how this works, but this can be as simple as removing lines, reducing the spectrum of colors, or eliminating data labels on every data point.
4. Make your visualization fit for a mobile phone
In the world today, there is a rapid increase in the number of people that use mobile phones. Hence, the demand for data visualization is also rapidly increasing. To be able to reach more number of people, you need to design and optimize your data optimization for mobile phones. In doing this, you will need to add to your data visualization design practices such as:
- Use of proper color coding
- Zoom-in features for graphs to show the detail of the data
- Avoid using graph titles and labels
- Put the most important information on the top left side corner
Always check how the end result looks on a phone if the visualization software you’re using allows for mobile-specific viewing.
Conclusion
In the world we currently are where there are numerous data sources and unorganized data, we can see that data visualization is a tool that is very useful in data analysis.
Data visualization has created an avenue where we can organize data and extract relevant and useful information when they are needed. Data visualization has also helped in providing an avenue where one can successfully and effectively pass data and information across to an audience of choice.
There is no doubt that if you can apply even a few of these principles governing data visualization then you are well on your way to building an effective data viz!
