In the fast-changing world, where most businesses make efficient decisions based on an abundance of data generated regularly. There is no doubt that businesses that can effectively harness this data have a significant benefit over those that cannot. To empower the potential of data, then, data visualization will come into play.
Data visualization is essential in communicating complex data using charts, graphs, and animations so that audiences can understand massive volumes of data clearly and compellingly. Moreover, data visualization often goes hand in hand with storytelling, which helps businesses yield actionable insights and make more impactful decisions.
In this blog post, we’ll dig deeper into the importance of data visualization and data visualization best practices to help take you to the next level.
Did you know that 90% of information transferred to the brain is visual, and the human brain processes visuals 60,000 times faster than words? Since the ultimate goal of data visualization is to effectively communicate patterns hidden within data in a clear, concise, and visually appealing way - you know the importance of data visualization in every organization. Here are some reasons why data visualization matters:
Businesses can show data in a form that is simple to grasp and interpret by using data visualization. Businesses can convey complicated data and insights in a way that is more understandable and available to a wider audience by employing charts, graphs, and other visual aids.
By giving users a clear image of the most important data and insights, data visualization can help users make better decisions. Businesses may make more informed decisions by using effective data visualization to spot patterns and trends that might not be visible in raw data.
Good Data visualizations may help businesses use their data to tell a more compelling tale because they are more interesting to look at than raw data. Businesses may captivate their audience's attention and boost engagement by appealingly visualizing data.
Businesses have a common understanding of important facts and ideas. Businesses can promote collaboration and communication among teams and departments by presenting data clearly and understandably.
Data visualization can help an organization's culture be more data-driven. Businesses can encourage staff to utilize data to guide decisions and adopt a more data-driven mindset by facilitating easier access to and engagement with data.
Now that you understand the importance of data visualization in your business. Why don’t you unleash it through the best practices for data visualization we mention below:
This is the most important part that we mention in most articles. Working with data is like telling a story. Therefore, to have good data visualizations, it is important to understand the specific goal and message that you want to convey to your audience at the beginning. For instance, the purpose of the dashboard is to showcase customer behaviors, quarterly revenues and profits, app traffic, and so forth. By doing so, the dashboard creation is smooth, the outcome is more valuable and less time-consuming.
After defining the goal, the next step is knowing who is the target audience you want to show your dashboards. These are crucial steps in creating effective data visualizations.
When it comes to your audience, let’s ask yourself some questions: “Are they experts in the field or are they newcomers?”. “What are their positions?”, “Are there any particular interests that need to be addressed?”. Conducting research and understanding your audience will help you select the best data visualization design for your audience.
Using effective data visualization like charts or texts helps effectively communicate your message. Here are some common types of charts and their usage to help better display data
Bar chart is used to evaluate contrasts between groupings or categories. The length of each bar represents the value of the category, like comparing the sales figures for different products in a retail store or comparing the number of visitors to different tourist attractions.
Line chart helps show trends over time. The data points are connected by lines, which makes it easy to see changes in the data over time. For example, it can be used to show the trend in a company's stock price over time or to show the change in average temperature over the course of a year.
Pie chart shows the relative sizes of different categories or groups. The area of each slice of the pie represents the proportion of the whole. In sales dashboards, you can use pie charts to present the breakdown of a company's revenue by product line.
Scatter plot demonstrates the relationship between two variables. The data points are plotted on a two-dimensional graph, with one variable on the x-axis and the other on the y-axis. An example of using this kind of chart is showing the correlation between the number of hours studied and exam scores.
Area chart is similar to a line chart, but with the area below the line filled in. Used to show changes in the total value over time. You can use an area chart to depict the change in a company's profits over time,
Heat map is used to show the distribution of a variable over a two-dimensional space. Each cell is colored according to the value of the variable in that location. For instance, it is used to show the concentration of pollution in different areas of a city.
When demonstrating charts, you should tell your stakeholders what they are about so that they can quickly understand the story you are trying to tell. Then, titles and labels come in handy.
One of the data visualization tips for using titles and labels is ensuring it is clear and concise, descriptive and consistent. For titles, prioritize simple text fonts, font sizes, and readable colors. Let's think about the context of what the graph explains to audiences when they read through the titles. About labels, avoid using too many labels that are put close together. Its effect is making your stakeholders hard to understand. Another data visualization tip when displaying labels is that don’t use abbreviations if it is unnecessary. If you have to, insert their meanings in a key within the dashboard.
Another best practice for data visualization is to apply suitable colors to your dashboard. The right colors can help emphasize key information and improve the readability of the dashboard, while the wrong colors can be distracting or even confusing.
When selecting colors, it is important to consider the association between colors. For example, Typically, green denotes positive things whereas red denotes negative ones, and Red is frequently used to denote focus. People usually focus their attention on it immediately because it is one of the most noticeable hues. Make sure your audience is not misled into thinking that red denotes the negative, though, when utilizing this hue to highlight something or draw a contrast with other colors.
In some scenarios, color contrast can be applied to your data visualization design. People tend to deliberately utilize the contrast of color to make the dashboard stunning, yet, make it too colorful that somehow your audiences don’t know where to concentrate. Let’s ensure that there is enough contrast between text and background colors to make the information easy to read.
One of the data visualization tips we want to emphasize but most people tend to skip, is making sure the access accessibility standards for viewers who may have visual impairments like color blindness. Hence, you know what color you should apply to your dashboard.
To provide context to help the audience understand the data, you can use annotations to explain more of your ideas, but make sure that it’s not too much since your dashboards will be clustered and indigestible. Adding additional visualizations like images, shapes, or arrows can be considered, but again, don’t overuse them. Keep your dashboard simple and clean enough to better deliver your messages to your stakeholders.
All of your efforts in building interactive dashboards will go to waste if the data is unclean. Before visualizing your data, let’s check for missing data points, remove duplicates, identify outliers, standardize and validate data, and do many more steps. Ensuring data is clean helps data analysis and visualization are accurate and reliable.
Another aspect we want to mention is data quality. It’s really important in creating data visualizations. Remember that the main purpose of data visualization is to help make faster and more efficient decisions. Therefore, no matter if your dashboard is beautiful, or the data is stale and outdated, your dashboard will bring zero benefits, not to mention may result in inaccurate decisions.
Data visualization is key to translating data into insights, helping make better decisions, and boosting business growth. Following best practices for data visualization not only saves your time building a dashboard but also makes you become a pro
Dataflake is a highly customizable data visualization tool that helps small and medium sizes create and customize visualizations with many styling options. You can use Dataflake along with advanced embed dashboards to apps or webs and data ops automation features. Try it out!
