How do I do data report analysis? How to do a data analysis report

To make a good data analysis report, it is enough to determine the reporting framework, the acquisition of data sources, data processing, data analysis, and visual display.

Determine the reporting framework

First determine the main structure of the analysis report, only a clear structure, can plan the theme of the entire report, and the structure can be clear to the reader at a glance. At the same time, it is necessary to find the right arguments and arguments, so that they can reflect strong logic.

Acquisition of data sources

Data sources are the basis of data analysis, and many analysis reports lack scientific basis and poor logic when mining and collecting data, so it is important to ensure correct and comprehensive data sources.

Data Processing

The purpose of data processing: to extract valuable and meaningful data from a large amount of disorganized data to solve problems. Filter and remove redundant and duplicate data, complete missing data, and correct or delete erroneous data.

Data analysis

The conclusion is clear and concise: the conclusion should speak according to the data, and strive to make the conclusion rigorous and professional. Every analysis has a conclusion, and the conclusion must be clear, the analysis conclusion should not be too much but precise, the analysis corresponds to the most important conclusion, the analysis is to find the problem, as long as the major problem is found, the goal will be achieved.

Rigorous derivation process: Analytical conclusions must be based on rigorous data analysis and reasoning process, and there can be no speculative conclusions, because subjective things will not be convincing.

Practical application: The data analysis report should be objective and fair, find problems and propose solutions. Since you can find the problem and the cause of the problem more clearly than others by understanding the product and doing an in-depth analysis on the basis of your understanding, then on this basis, the suggestions and conclusions made based on your own knowledge can make the whole process very meaningful.

Visualization

When analyzing data, try to use data to speak, and use vivid charts and charts to display the analysis results of the report, so as to be able to display the conclusions more intuitively. So as to get a more convincing conclusion.

1.Be clear about your purpose and ideas

First of all, understand the purpose of this time, sort out the analysis ideas, and build an overall analysis framework, decompose the analysis purpose, and turn it into a number of points, which are clear and clear, that is, the purpose of the analysis, what kind of users, how to carry out data analysis, which angles need to be analyzed, and what analysis indicators are used (all kinds of analysis indicators need to be reasonably used). At the same time, ensure that the analytical framework is systematic and logical.

2.Data Collection

According to the purpose and needs, sort out the overall process of data analysis, find your own data source, and conduct data analysis, and generally data in four ways: databases, third-party data statistical tools, statistical yearbooks or reports of professional research institutions (such as iResearch Information), and market research.

3.Data Processing

There will be a variety of data in data collection, some of which are effective and some are useless, at this time, we need to process the data according to the purpose, which mainly includes data cleaning, data transformation, data extraction, data calculation and other processing methods, and process various raw data into intuitive and visible data that product managers need.

4.Data analysis

After the data is processed, data analysis is carried out, which is the process of using appropriate analysis methods and tools to analyze the processed data, extract valuable information, and form effective conclusions.

5.Data presentation

In general, data is presented in a graphical way. Commonly used data charts include pie charts, column charts, bar charts, line charts, bubble charts, scatter charts, radar charts, and more. Further processing and sorting into the graphics we need, such as pyramid charts, matrix charts, funnel charts, Pareto charts, etc.

6.Report writing

The report must be written in a comprehensive manner, clear and clear, and the framework must be clear so that the reader can understand it. A clear structure and clear priorities can enable readers to understand the content of the report correctly; ** It can make the data more vivid and lively, improve the visual impact, and help readers to see the questions and conclusions more vividly and intuitively, so as to generate thinking.

Look for data analysis tools, such as excel sheets, which are the most commonly used, and the various functions in them, such as how to create a data table and how to use it.

1. Investigate the person or object to be written, and organize the complete data.

2. Write down the data**, the purpose of the investigation, and the methods and methods of the investigation.

3. Organize the data into charts or bar charts, line charts, pie charts, etc., so as to see the characteristics of the data more intuitively.

Summary. Dear, one, the purpose of the analysis is still the old saying, before doing anything, think clearly about what the purpose of doing this is. Writing a data analysis report is the same, if you don't have a clear purpose at the beginning and start the analysis blindly, the final result is likely to be that the analysis is getting farther and farther away from the goal after analyzing for a long time.

Therefore, understanding the purpose of researching this thing is the first step to starting data analysis. Second, the dismantling of indicators to find problemsAfter clarifying our analysis purpose, we should disassemble the indicators according to our analysis objectives, and find problems by dismantling the indicators. That's a bit of an understatement, but let me give you an example.

Background: At the end of the year, a manufacturing company needs to conduct a business review of the sales line, so it needs to check the progress of the annual goal completion of each sales line personnel and give recommendations. At the same time, through statistics, it is found that the company's gross profit margin has declined this year, and data analysts need to find the reasons for the decline in gross profit margin through data.

Hello dear, glad to answer for you. Kiss, data analysis report how to do.

Dear, first, the purpose of clear analysis is still the old saying, before doing anything, think clearly about what the purpose of doing this coincidental thing is. Writing a data analysis report is the same, if you don't have a clear purpose at the beginning and start the analysis blindly, the final result is likely to be that you are getting farther and farther away from the goal after analyzing it for a long time. Therefore, understanding the purpose of researching this thing is the first step to starting data analysis.

Second, the dismantling of indicators to find problemsAfter clarifying the purpose of our analysis, we should disassemble the indicators according to our analysis objectives, and find problems by dismantling and solving the indicators. That's a bit of an understatement, but let me give you an example. Background:

At the end of the year, a manufacturing company needs to conduct a business review of the sales line, so it needs to check the progress of each sales line personnel in achieving the annual goals and give suggestions. At the same time, through statistics, it is found that the company's gross profit margin has declined this year, and data analysts need to find the reasons for the decline in gross profit margin through data.