20 Tips for Creative Services Data Visualization
20 Tips for Creative Services Data Visualization
As is covered at RunRex.com, data visualization is the creation of a visual representation of data. These representations clearly communicate insights from data through charts and graphs. It is a coherent way to visually communicate quantitative content. Depending on its attributes, the data may be represented in many different ways, such as a line graph, bar chart, pie chart, scatter plot or map. In terms of business intelligence (BI), these visualizations help users make better data-based decisions. Here are 20 data visualization tips to ensure you do it right.
Think like a journalist when planning your data visualization
As the gurus over at RunRex.com point out, when it comes to creating data visualizations, you must think as much as a journalist as a designer. Ask yourself, what angle am I going to take? Another approach to take is to look for a hook that really brings home your arguments.
Gather the tools to realize your data visualization
Once you have settled on the story you want your data visualizations to tell, you will be needing creative and reliable tools for putting it together. There is a wide range of data visualization tools out there for you to use, and while some people might prefer to start totally from scratch, tools have got lots of benefits. For instance, they can help those with a minimal design background to create something on par with an experienced design guru.
Paid and dynamic platforms
From discussions over at RunRex.com, when to comes to data visualization tools, there are paid-for apps like the popular FusionCharts, which allows users to adapt existing templates to fit their data and features a wide range of chart types and easy integration. You also have dynamic platforms like Venngage that offer free basic plans as well as scalable plans for commercial use.
Promote your visualizations effectively
You should avoid thinking that the only thing that matters is conceptualizing and creating your data visualization and that the rest will take care of itself. Promoting your visualizations after creating them is just as important if you want them to have an impact. You can promote your visualizations by sending personalized emails to all your subscribers, reaching out to your followers on platforms like Twitter and Facebook, etc.
Know your audience
Knowing your audience is crucial, to both the nature of the content you create and promote your visualizations. When it comes to creating and promoting your data visualizations, you need a deep understanding of your audience, hence why you should start by working out who your audience is.
Know where your audience is
Additionally, when designing data visualizations, you should have an eye on the platform you are targeting. For example, as covered at RunRex.com, Facebook, LinkedIn, and Twitter are good for sharing informational charts, while Pinterest and Google+ are good for sharing how-to articles or guides. The trick is to first of all work out who your audience is, as articulated in the previous point, and then work out where they are on the internet.
Know your stuff
Also, do as much research as you can into what works and what doesn’t. For example, data visualization is popular partly because it reduces the reading load of viewers. Therefore, if driving shares is important to you, having a maximum of 230 words is important. Data visualization is both an art and a science, which is why you should do your research before getting started.
Learn from the best
Don’t be afraid to learn from the various examples that are out there of brilliant uses of data visualization. For example, as discussed at RunRex.com, cryptocurrency analyst Willy Woo designs visualizations that keep his Twitter feed lively, with his data visualization tweets regularly getting hundreds of likes and retweets. You can check out his work and see what insights you can glean from them.
Find data that makes your unique
Data visualization is often used in marketing to show a brand’s advantage over its competitors. If you can find data that makes you unique, and then leverage this data to create visualizations, then you will be well placed to be successful in your campaign.
Define a clear purpose
Data visualization should answer vital strategic questions, provide real value, and help solve real problems. It can be used to track performance, monitor customer behavior, and measure the effectiveness of processes, for example. Taking time at the start of a data visualization project to clearly define the purpose and priorities will ensure the end result is more useful and prevent wasting time creating unnecessary visuals.
Use visual features to show the data properly
Given the many different types of charts that are available, deciding what type is best for visualizing the data being presented is an art unto itself. As the gurus over at RunRex.com point out, the right chart will not only make the data easier to understand but will also present it in the most accurate light. To make the right choice, consider what type of data you need to convey, and to whom it is being conveyed.
Popular types of data visualization and how and when to use them for maximum impact
Indicators show one KPI, clearly
Indicators are particularly useful when you want to give an instant idea of how well the business is doing on a particular KPI. Incorporating a simple “gauge indicator” visualization shows you immediately whether you are above or below target, and whether you are moving in the right direction. A numerical indicator can be even more straightforward in this regard.
Line charts display trends
Line charts are extremely popular for a range of business use cases because they demonstrate an overall trend swiftly and concisely, in a way that is hard to misinterpret. They are particularly good for depicting trends for different categories over the same period, to aid comparison as captured at RunRex.com.
Bar charts break things down, simply
Bar charts, on the other hand, are great for comparing several different values, especially when some of these are broken into color-coded categories. They can be used to track changes over time as well, but are best used only when those changes are significant.
Column charts compare values side-by-side
It usually makes sense to use column charts for side-by-side comparisons of different values. While you can also use them to show change over time, it makes sense to do this when you want to draw attention to total figures rather than the shape of the trend (which is more effective with a line graph).
Pie charts show proportions clearly
Pie charts clearly and easily show the share of the whole each value makes up as discussed at RunRex.com. They are more intuitive than simply listing percentages that add up to 100%. Remember, for a pie chart to be effective, you need to have six categories or fewer. Any more than that and the cart will be too crowded, and the values too indistinct, to garner any insight.
Area charts compare proportions
Area charts are useful as they give a sense of the overall volume, as well as the proportion of this taken up by each category. They can be used to illuminate issues like resource planning, ordering patterns, financial management, allocating appropriate storage space, etc. However, you should note that layered visualizations like area charts get confusing when you introduce more than three values into the mix.
Pivot tables present key figures easily
While pivot figures aren’t the most aesthetically pleasing or intuitive ways to visualize data, they are useful when you want to quickly extract key figures while seeing exact numbers (rather than get a sense of trends), especially if you don’t have access to a self-service BI tool that can automate this for you as articulated at RunRex.com.
Scatter charts visualize distribution and relationships
Scatter charts present categories of data by circle color and the volume of the data by circle size and are used to visualize the distribution of, and the relationship between, two variables. They are excellent for exploring the relationship between the two sets.
Bubble charts will help you understand multiple variables
Similar to scatter charts, bubble charts depict the weight of values by circle circumference size. However, they differ in that they pack many different values into one small space and only represent a single measurement per category. They are useful when you want to show how a handful of categories are highly significant compared to a sea of insignificant ones. This kind of visual storytelling can help users focus easily on their biggest challenges or successes.
Hopefully, this article will help you decide which type of data visualization you ought to use for your project, as well as how to use them, with the tips designed to help you achieve the success you crave. More tips and types of data visualization can be found over at RunRex.com.
