Before the concept of big data visualization appeared, there was already a wide range of applications for data visualization, from demographic data to student performance statistics, all of which can be visualized to explore the patterns. Today, information can be visualized in a variety of ways, each with a different focus.
Characteristics of data:
Data visualization, you need to understand the data first, and then go to master the visualization method, so that you can achieve efficient data visualization. When designing, you may encounter the following common data types:
Quantitative: data is measurable and all values are numbers
Discrete: numeric data may take values in a limited range. For example: the number of employees in an office
Persistent: data is measurable and within a limited range, for example: annual precipitation
Ranging: data may be categorized based on grouping and classification, for example: production, sales
Traditional data visualization is dominated by a variety of general-purpose charting components, which do not allow for cool, mind-blowing visual effects. Excellent data visualization design needs to have cool visual effects to make the visualization design stand out anytime, anywhere. This time with the addition of three-dimensional elements to create a sense of space can greatly increase the level of the picture, and can be observed in multiple dimensions, each angle may produce a stunning visual experience. The following is a picture of some 3D design cases done by Hightopo:
Note: Hightopo
There are many cases of large screen design that involve the integration of two-dimensional and three-dimensional design, which requires overall consideration of style consistency. Style consistency can be achieved from the color tone and the use of elements to achieve unity, no sense of contradiction.
Figure Note: Tupou Software
Figure Note: Tupou Software