I have read a lot of articles about data visualization, but the explanations may be one-sided. The purpose of data visualization is to assist data analysis. So what are data visualization and visualization analysis?
In an increasingly data-dominated world, a variety of users are collecting data in a variety of ways, and everyone wants to learn more valuable information from all their data to assist the management of the enterprise or individual ; Data visualization and visual analysis are ways to help us better understand or extract data information.
Data visualization and visual analysis are actually two new terms, and the development in China is only a decade or two; many people may still understand it literally, and its in-depth concepts, advantages and data It is not clear how visualization and visualization work together; so I want to focus on sharing my personal understanding of both in this article.
1. Data visualization: draw data charts or large data screens
In short, data visualization means displaying data information in the form of visual charts, making it easier for human users to understand insights.
Data is usually displayed in the form of graphs or charts, such as charts, graphs, lists, maps, and large screens of comprehensive data that integrate these multiple formats.
The main purpose of data visualization is to clearly convey the meaning of data, help explain trends and statistical data, and display real-time trends in data that cannot be seen in the text reports of past data analysis.
The use of data visualization can help us strengthen the interpretation and understanding of data information, and it is expressed in the simplest possible chart visualization form, making it easier for us to obtain insights from data; when data analysis users want to view the analysis results and quickly When they understand the data, they can use data visualization.
Visualize the analysis results of the data and reveal the data patterns and trends, so as to perform "heavy work" on the data, so that users can check the data, understand the meaning of the data, explain its highlighted patterns, and help them get rid of the complexity. Find meaning and gain useful data insights in the data set.
Static data visualization chart "Baidu Gallery"
Three-dimensional data visualization large screen "Kangaroo Cloud EasyV"
2. Analysis and visualization, which are the key to digital transformation
The relationship between data visualization and visual analysis is symbiotic.
This relationship is illustrated in the study of the "perception cycle" of the analytical reasoning process by American scholars James J. Thomas and Kristin A. Cook:
Good data visualization makes visual analysis more effective and shows better insights to users, while better insights make visualization more attractive; it is easier for users to better understand their data and jointly help companies and individuals determine How to improve efficiency, increase revenue and gain a competitive advantage over competitors.
3. The role of visualization in analysis
Data visualization can be static or interactive:
- Static visualization provides users with a single view in front of them;
- The large interactive data visualization screen enables users to delve into the data and extract and inspect various views of the same data set to select specific data points that they want to view in a visual format.
Large data visualization screens can make data-driven insights clearer and can enhance the understanding of the entire organization.
In the above figure, it is shown that visual analysis is the basis of the interactive data visualization large screen, thus demonstrating the connection between the two; data analysis is the source of data visualization display, and displays data by linking visual models and charts. Analyze the results.
4. Visualization: Past, Present and Future
In a nutshell, there are three types of visual analysis: descriptive, normative, and predictive; the simplest type is descriptive analysis, which describes what has happened and suggests its root causes.
Normative analysis can take things to the next level: in addition to helping companies understand the reasons, it also helps companies learn from what has happened and formulate strategies and strategies that can improve their current performance and profitability; a simple example is right Analysis of marketing activities.
Predictive analysis is the most beneficial, but arguably the most complex type. It can help users identify patterns that suggest future situations and behaviors; using predictive analysis, organizations can plan upcoming programs, predict new trends, and optimize for them. Effective and most cost-effective preparation; anticipating upcoming trends lays the foundation for optimizing the organization’s benefits, and using visualization to make more informed decisions.
The case as shown in the figure below:
Generally speaking, the data obtained in the large data visualization screen comes from multiple sources: structured data (in the form of relational databases such as Excel) or unstructured data (from text, video, audio, photos, the Internet, and smart devices) ).
Collect this data on local servers, or increasingly in cloud databases; they are converted into data visualization and shared through large screens and analytical applications, so that users can make more informed, data-driven decision making.
The task of the data team and the business and analysis teams is to choose and develop the best way to visualize data and build a well-organized data screen to help end users make more informed decisions; the data must be clear, easy to understand, and easy to drill. In order to find deeper insights when needed.
If you want to combine data visualization and visualization analysis, you naturally need a data visualization display and analysis platform that can powerfully combine visualization analysis and data visualization functions; it can handle local storage, cloud storage, or storage in both The ability of a large amount of data; can flexibly integrate data from any source; and has the sustainability of future growth.
Five, visual analysis and data visualization
In the past, many companies’ marketing activities have been using static data reports to propose corresponding solutions to problems, but this is very inefficient in terms of time; but when you replace static charts with pre-configured data visualization The large screen or the bi-report dynamic table can also adjust the marketing strategy based on the data analysis results in real time to double the sales revenue while improving work efficiency.
Including this year's fight against the new crown epidemic, news reports and statistics have used a lot of visualization for analysis. The following large screen is a picture of the spread of the virus in the UK.
It provides local and regional national health service capacity planners with the real-time information they need to use resources in areas with more serious outbreaks or areas with high-risk patients. The level of detail of the data is related to the patient's list in the family doctor's personal surgery. The same.
In order to get the best insights from data and get the most benefits from data analysis, it is necessary to seamlessly combine visual analysis and data visualization-both are important, but they cannot function without each other; they are both analyzing and Understanding your data and using the insights they reveal play a vital role in formulating a successful future strategy for your business.