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5 techniques for better data visualization
Data visualization is a form of communication that portrays dense and complex information in graphical form. When I design the data and want to translate the data number into a graph. I faced challenges. How do represent the data while being able to leverage human cognition to communicate quantitative information quickly? What are the best practice and principles to express data of varying types, and sizes and help users navigate them with context? As a UX designer, I know my job needs to find powerful solutions to flight those challenges.
I went to read and learn courses. I tried to find a pattern in data visualization that use in design and well-telling stories. This article here is summarized the reading of the book Storytelling with Data: A Data Visualization Guide by Cole Nussbaumer Knaflic, Fundamentals of Data Visualization by Claus O. Wilken, a course of data visualization for business from my company's learning center(Cisco), and many online blog posts I read about data visualization In the past few months.
My goals in learning data visualization enable the user experience design to express data from the scale of a few data points to large multi-variant data sets, and to well-prioritize data accuracy, clarity, and integrity. In the end, the user interface design can present information that doesn’t distort meaning and help users to navigate the data with context and affordances that emphasize exploration and comparison. Ultimately, achieving the dataset can help users in quick decision-making and take action.
I summarized them into 5 key points here, that combined human cognition, business storytelling, and data visual storytelling. As we all are UX designers, not too visual design-driven(compared to visual designers), and not too business-driven(compared with product managers), I hope those 5 important tips can help you to represent your dataset at a high level of touching the points of both sides.
1. Design for specific audiences and their needs
Creating nice data visualizations is similar to designing the user experience for a product. The first step is empathy with users and considering who is your target users and their pressing needs.
