Data requirements collection.
Data Collection. Data cleansing.
Data analysis. Explanation of the data.
Data visualization.
After sorting, clarifying and analyzing the series of data, the problems and trends of the data connotation are presented through visualization. Humans are visual creatures and have a greater sense of icon color, so visualization can make the data easy to understand.
If it is saidData analysis. It's in big dataExcavators, thinkers, thatData visualization. It is to make the analyzed data more intuitive, easy to read, and more efficient.
Data visualization is like oneSpeaker, through a more popular way to make the data more people understandable, lower the threshold for reading information.
Data visualization is very common in everyday life;They usually come in the form of charts. In other words, the data is displayed graphically so that it is easier for the human brain to understand and process. Data visualization is often used to uncover unknown facts and trends. By observing relationships and comparing data sets, a way can be found to find meaningful information.
In the world of big data, data visualization tools and techniques are essential for analyzing large amounts of information and making data-driven decisions.
The picture comes from the official website of Yizhiwei.
A good data visualization platform should have bothData source access capabilities, resource management capabilities, visual application management capabilities, visual application construction capabilities, system integration capabilities, and security management and control capabilities
Thomas Schleicher's 2012 paper entitled "When is good news really good news?".It was found that middle managers often pick at favorable data points or resort to vague language when reporting bad news to their superiors. Schleicher found that this selectivity and avoidance had significant consequences:
Misreporting data or distorting data visualizations can lead to bad decisions from superiors with incorrect or missing information.
The financial performance of an organization that does not report data correctly is worse than that of an organization that has the right information.
Obscuring the hard truth has a dangerous effect on every business in the study.
Data visualization is very powerful, and how it is leveraged in an organization or business can have positive or negative consequences. Incorrect data visualization can affect decision-making and obfuscate messages, but properly applied data visualization will do everything more effectively: strong messaging, clearer insights, and decisions that can be supported.