With the vigorous development of the big data industry, many enterprises have begun to apply data visualization.
More and more industries such as smart cities, smart transportation, and smart medical care have the demand for visualization, and the visualization Buy email list industry has also ushered in a rapid growth period.
Interpretation of data visualization: Data visualization is to interpret and convey data information clearly and effectively by means of "visualization", which is relatively complex, abstract, and we can't understand, and helps us discover the data. Laws and characteristics, mining the value behind the data.
Large-screen visualization: The large -screen visualization is a data visualization design with a large screen as the main display carrier. Its application scenarios are not extensive, such as ToC, ToB, ToG, etc.
It is generally used in important places such as conference exhibition halls, park management, urban traffic dispatch centers, public security command centers, and enterprise production monitoring.
The visual user group is relatively clear, mainly unit leaders and some front-line personnel. Through interactive real-time data monitoring, we can gain insight into operational growth and facilitate intelligent and efficient decision-making.
With the development of the industry, visualization has also been subdivided in the industry.
Some common categories:
Industry visualization ( such as transportation, medical care, finance, military and police forces, agriculture, factories, chemicals, etc.);
Intelligent terminal system (customized terminal products);
Demonstration demo ( data presentation, exhibition display, data kanban);
Visual analysis system (aided decision-making through data analysis and monitoring, such as traffic warning platform, weather monitoring platform, etc.) .
1. Market Status
Due to the increasing demand for visualization in recent years, general companies will have some visualization needs, and major manufacturers have gradually integrated visualization resources to achieve platformization and low-code.