Regardless of industry or purpose, every organization relies on data to one extent or another. Data points feed business strategies and decision-making capabilities and give organizations a fundamental understanding of their business or applicable markets are performing.
However, while raw structured or unstructured data on its own can provide critical insights for a business, the real value comes when being able to visualize key metrics and trends. Data visualization, or charting your data, helps organizations to understand complex data points in an easy-to-understand format. More than that, however, charts and graphs help viewers to uncover potentially hidden trends or patterns in metrics that may be hard to spot in databases or spreadsheets.
However, there are right and wrong ways to go about charting your data so that you’re able to gather the correct information without overcomplicating or oversimplifying the format. Below we’ll address some of the do’s and don’ts of charting your data.
Do Choose the Right Charts for the Job
Regardless of what data visualization platform or plugins you choose to use, there is no shortage of ways to chart the information you need to analyze. However, deciding whether to use a bar graph, scatter plot, histogram, or any other visual data tool should depend on the type of information you wish to present.
Not every type of chart can give you the level of granularity or depth you need, and it’s important not to try and force data into a graph where it doesn’t belong. Remember to use the right tool for the job and choose a chart that is easy to customize, understand, and update regularly. Most importantly, your chart should help you turn data into action.When charting your data, it’s important to continuously ask yourself how and why the data visualization is useful for your business. This will ensure your data insights are actionable. Click To Tweet
Don’t Rely Heavily On Pie Charts
While pie charts have their place in certain situations, they are often overused in presentations, reports, and dashboards. Even though pie charts can be a great way to quickly and easily visualize various data points relative to one another, they can quickly become hard to read, and their value diminishes over time.
As more data points and labels are added to a pie chart, it can become challenging to read and understand. Unless sacrificing large amounts of real estate on a report or spreadsheet, smaller data points or percentages can become indistinguishable from one another. Depending on the analyzed data, certain pie charts can potentially hide significant increases or declines, inadvertently misleading the viewer unless they have the raw data points to reference the graph against.
Do Use Appropriate Labels
Labels are an essential element to any data chart or graph. The concept of charting your data is to present a visualization tool that eliminates questions about the information and how it is represented in relation to other data reference points.
Your labels should be static and not easily manipulated or relocated on the chart as your data is updated. Display a chart title, or purpose, at the top of the chart, and identify chart information along the X and Y-Axis. How you choose to label your data will also help you decide on the correct type of chart to work with, as certain graphs are more manageable when labeling multiple datasets than others.
Don’t Make Your Data Cluttered
A common mistake that many people make when trying to chart their data is deciding to use a one-size-fits-all approach. Many data visualization elements are designed to support multiple data points and present them in one chart. However, over time this can lead to a cluttered graph with too much information to process without further analysis.
A better approach is to separate your metrics into different but supporting graphs when working with multiple data elements. Rather than taking up your entire dashboard with one large chart, break the data up into two or three charts that segment datasets. This allows the viewer to quickly focus on the information that matters most to them without succumbing to information overload.
Do Use The Right Colors
While choosing the right chart type to visualize your data, it is equally important to get your data to stand out. A great way to do this is by injecting color into your charts. But rather than just making your charts look appealing, there are strategic ways in which you can use color to help better describe the data you are showcasing.
By using colors logically, you can better differentiate between increases or declines in the data over time. Using greens and reds to denote positive or negative trends can be a great way to identify areas of interest in your charts. When charts measure year-over-year performance, it’s also a good idea to use varying color palettes, which will help avoid confusion when calculating relevant data versus historical.
When creating charts, especially ones to be presented to multiple parties, there can be a tendency to overdo the data visualization. Animated and dynamic charts can help bring data to life and can be an important part of interactive demonstrations and boardroom discussions. However, if you’re not careful, overly complicated charts with too many bells and whistles can distract from what the data is actually showing you.
When it comes to charting your data, taking the “less-is-more” approach is best. Removing unnecessary chart elements like gridlines, backgrounds, dark borders, or other cosmetic aspects of the graph simplifies its design and brings the focus back where it belongs – on the data itself.
Do Tell a Story
One way charts can truly be effective is if they are designed from inception specifically to fit their audience. Much like a storyteller focuses on hooking an audience’s attention and keeping it throughout the storyline, your data visualization strategy should do the same. This can be achieved by ensuring whoever is viewing the data can easily comprehend the purpose of its use.
Much like a story, your charts should be clear and concise, focused, relatable, and, most importantly, actionable. To get this format right, it’s essential to ask yourself key questions before deciding how you should chart your data. These questions can include, “what is the problem I’m trying to solve?”, “what type of information do I need to solve it?”, “who is this information most applicable to?”, and “how can I make my data actionable?”
When charting your data, you can use a number of different formats and techniques. However, by understanding the do’s and don’ts of data visualization, you’ll keep your metrics actionable and avoid the pitfalls of overcomplication.