Defining the purpose and thinking of data analysis is the first condition to ensure the effectiveness of data analysis process. Its function is to provide a clear direction for data collection, processing and analysis. It can be said that thinking is the starting point of the whole analysis process. First of all, unclear purpose will lead to the wrong direction. In the case of clear purpose, it is necessary to construct an analysis framework, and decompose the analysis purpose into several different analysis points, that is, how to conduct detailed data analysis, from which angles to analyze and which analysis indicators to use.

Step 2 collect data

Collecting data is a process of collecting relevant data according to a certain data analysis framework, which provides materials and basis for data analysis. The data mentioned here include primary data and secondary data. First-hand information mainly refers to the information that can be obtained directly, and second-hand information mainly refers to the information obtained after processing.

Step 3 process data

Data processing refers to the processing and sorting of collected data to form a style suitable for data analysis, which is an essential stage before data analysis. The basic purpose of data processing is to extract and deduce valuable and meaningful data from a large number of disordered and incomprehensible data. Data processing mainly includes data cleaning, data conversion, data extraction and data calculation.

Step 4 analyze the data

Analyzing data refers to the process of analyzing the processed data with appropriate analysis methods and tools, extracting valuable information and forming effective conclusions. Because data analysis is mostly done by software, it requires data analysts to not only master various data analysis methods, but also be familiar with the operation of data analysis software. Data mining is actually an advanced data analysis method, which is to mine useful information from a large number of data. According to the specific needs of users, it finds out the required information from massive data to meet the specific needs of users.

Step 5 display data

Generally speaking, data are presented in the form of tables and charts, which is what we often mean by using charts. Commonly used data charts include pie chart, column chart, bar chart, line chart, scatter chart and radar chart. Of course, these charts can be further sorted to make them the graphics we need.

Step 6 write a report

The data analysis report is actually the summary and presentation of the whole data analysis process. Through the report, the reasons, process, results and suggestions of data analysis are presented completely for decision makers' reference. A good data analysis report, first of all, needs to have a good analysis framework, and illustrated, clear level, so that readers can see at a glance. In addition, the data analysis report needs a clear conclusion. Analysis without a clear conclusion is not analysis, and it also loses the significance of the report, because we originally analyzed it to find or verify a conclusion, so don't go to the end. Finally, a good analysis report must have suggestions or solutions.