In the digital age, big data has become an integral part of business, science, government, and everyday life. However, big data itself is often boring and difficult to understand numbers and words. If there is no effective way to visualize it, valuable information will be missed. Here are some ways to turn boring big data into engaging visualizations and animations.
First, choose a data visualization tool that suits your needs. There are many powerful tools to choose from on the market. Here is a free data visualization large-screen software-Mountain Sea Whale Visualization. Shanhaiwhale visualization not only supports access to multiple data sources such as GIS data, but also migrates Cesium projects at ultra-low cost through Shanhaiwhale Cesium. Shanhaijing visualization not only realizes the integration of digital twin system and GIS, but also can import custom 3D models and various visualization components, and can also realize real-time monitoring of equipment status through API interface and IOT data interface.
Big data is often irregular and disorganized. Data must be cleaned and prepared before it can be visualized. This includes removing duplicates, filling missing values, converting data to an appropriate format, and more. Clean datasets are easier to turn into attractive visualizations. Different types of data are suitable for different types of charts. For example, bar charts are good for comparing different categories of data, line charts are for showing trends, scatter charts are for showing relationships between data points, pie charts are for showing the ratio of parts to a whole, and so on. Choosing the right chart type is important to conveying information accurately.
Interactivity can make visualizations more engaging and useful. By adding interactive elements, users can interact with the data, such as zooming, filtering, viewing details, etc. This allows users to explore the data more deeply to gain more insights. Colors and labels can enhance the information conveyed in a visualization. The right use of color can highlight important data points or trends, while labels can provide additional information. But be careful not to overdo it with color, which can create confusion.
Animations are one of the ways to turn static visualizations into engaging ones. It can be used to display time series data, trends in data, or changes in data across different dimensions. Animations can make data more vivid and easier to understand. Last but not least, explain your visualizations and animations to your audience. Provide short titles, legends, and notes to help viewers understand the message you are trying to convey.
Presenting boring big data as visual graphs and animations can make the data easier to understand and more engaging. Choosing the right tools, data preparation, chart types, interactivity, colors and labels, animation effects, and explaining to your audience are all critical steps to successful data visualization. This will help you gain valuable insights from big data and better support decision making and messaging.