Tons of data are exchanged every second, so- What is your opinion that businesses can have deeper insights into their vast data?
The best solution is- Data Visualization Design. It helps recognize patterns, errors, and red flags, identify weak points, and extract valuable insights. Data visualization’s sole objective is to help businesses make informed decisions to take business a step ahead.
Here visualization refers to the pictorial representation of the data that gives a clear view. For a business, data is everything. The visualization is beneficial for:
- Data analysis
- Faster decision making
- Simplifying complex data and more.
A business can leverage the data visualization design by improving it. If you want to know how to improve your data visualization design, then continue with this blog.
Let’s start with some basic information!
What Is Data Visualization Design?
Data visualization stands for graphical representation of data, where the process turns raw data into forms of maps, graphs, and infographics. The design that represents it is called data visualization design. Visualization’s sole advantage is offering a seamless way to visualize the trends and data patterns via extraction from the data chunks.
The prime objective of data visualization techniques is to represent the data to end users in an easy format. You will be surprised to know that the human brain responds to visuals instead of text. Some tools are available that help with better data visualization, such as Power BI, Tableau, Zoho Reports etc.
These tools can help derive insights to take customer experience to the next level. Additionally, data visualization is considered a key part of the strategy to unleash the hidden qualities of data.
The Process of Data Visualization
A question might arise in the reader’s mind: what is the data visualization process? So, the process works like this:
- Goal of research
Here you need to identify the research goal, what kind of data is needed and what kind of visualization you need to communicate your research.
- Fetch the data
Get access to the large data set. Manually it will be a daunting task, so you can take the help of APIs, scrape data from the internet, or use tools to collect the data, such as Power BI Dashboard.
- Data Cleaning
It helps in the easy visualization of data because clean data remains free from error and makes the process easy. It saves time instead of fixing the issue while visualizing the data.
- Choose A Chart
Data charts are the best options for data visualization and effectively convey the message. Here you need to pick the chart that matches your needs carefully.
- The Tools
Multiple tools are available for processing the data, and some of the legendary tools available are Tableau and Power BI. Suppose you have less budget. You can start with free tools like Power BI Desktop.
- Prepare Your Data
Data preparation includes multiple steps such as formatting columns, value conversion, filtering, grouping, and combining variables.
- Create Chart
The final step is chart creation which also holds key steps such as data import into the software, selecting chart type, and more.
Until this section of the blog, we have gone through crucial information about data visualization design. So, it’s time to look at the top ways or tips to improve data visualization design.
Top-10 Tips to Improve Your Data Visualization Design?
The tips mentioned in this section also represent the data visualization best practices that can help you a lot. So, let’s start.
#1. Choose A Suitable Chart
The first best practice for storytelling via visualizing the data is choosing a suitable chart as per needs, as a universal size can fit all. You can also combine the related charts for the best effects. Some popular formats are bullet charts, bar charts, line graphs, maps, and pie charts.
#2. Colors for Data Representation
Colors play a crucial role in making data visualization design more appealing, so choose it with some intention. If you want to show data growth, then using warm colors is the best, or you can use light colors to represent the less growth to represent less growth. The only condition is that colors must match the intended message you want to deliver.
#3. Data Labels & Annotations
Using data labels and annotations to improve the data visualization designs is crucial. It helps in creating an easy understanding among the end users. The labels help in recognizing the data points, and on the other side, annotations provide additional information.
#4. Predictable Patterns
Unpredictable patterns can destroy the whole visualization. The reason is if patterns are complex or random, then users will find it difficult to understand and fail to get what they want from the data. So, one of the data visualization techniques is to use a predictable pattern.
#5. Alignment
Align data elements in an appropriate format to create the best effect of data visualization design. The correct alignment will help the users navigate from one section to another easily. Here you can use the basic technique, such as aligning the data on X and Y axis, but all must be relevant to each other.
#6. Use of Appropriate White Space
The appropriate white space will assist you in making visualization smooth. It helps in balancing the information showcasing, including the other colors. You can show the crucial data in colors and put other data in whitespace for clear visibility.
#7. Reduced Chart Junks
If you plan to create a data visualization design for the best experience, limiting chart junk is one of the best ways. It works by removing the unnecessary or distracting elements that do not relate to the message you want to convey.
#8. Visual Hierarchy
The only objective of data visualization design is to represent the data in an understandable format and to engage the customers. One of the best ways to do it is to represent the data in a visual hierarchy so readers can move from top to bottom or vice versa effortlessly to view the desired data. Here BI tools work fantastic for example, one of the best benefits of Power BI is to represent the data in a visual hierarchy.
#9. Highlight Patterns
Using shapes is the best method to highlight the data patterns and relationships. The shapes can be anything such as a circle, square, triangle, cube or any shape else. With the help of shapes, you can showcase data overlapping or increasing or decreasing.
#10. Consistent Size
Whatever charts, graphs, or shapes you are using for data visualization design, its size must be consistent. It will create clarity instead of confusing the readers’ eyes. For better visualization, clarity is a must.
The Final Thoughts
There is tough competition in the market where multiple brands are competing. Here data visualization can help a lot to identify the weak points you can work on to have a strong presence. By improving the data visualization design, you can create a better effect. The tips mentioned above can help you with it. For better effect, you can consult with the experts or take the help of professionals from top Power BI development companies or companies with vast experience. So, without any delay, take the right decision at the right time to add value to your business with the help of data processing and visualization.
Featured image by rawpixel.com on Freepik
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