The premise of engaging in data analysis is to understand the business, that is, to be familiar with the industry knowledge and the company's business and processes, and it is best to have your own unique opinions. If it is divorced from the industry cognition and the company's business background, the analysis result will only be an off-line kite with little use value.

Step 2 manage

On the one hand, it is the requirement of building a data analysis framework. For example, the theoretical knowledge of marketing and management is needed to guide the determination of analysis ideas. If you are not familiar with management theory, it is difficult to build a data analysis framework, and subsequent data analysis is also difficult. On the other hand, the function is to put forward guiding analysis suggestions for the conclusion of data analysis.

Step 3 analyze

It refers to mastering the basic principles of data analysis and some effective data analysis methods, and applying them flexibly to practical work in order to effectively analyze data. The basic analysis methods are: comparative analysis, grouping analysis, cross analysis, structural analysis, funnel diagram analysis, comprehensive evaluation analysis, factor analysis, matrix correlation analysis and so on. Advanced analysis methods include: correlation analysis, regression analysis, cluster analysis, discriminant analysis, principal component analysis, factor analysis, correspondence analysis, time series and so on.

Step 4 use tools

Refers to mastering common tools related to data analysis. Data analysis method is a theory, and data analysis tool is a tool to realize the theory of data analysis method. Faced with more and more huge data, we can't rely on calculators for analysis, but must rely on powerful data analysis tools to help us complete data analysis.

Step 5 design

Understanding design refers to using charts to effectively express the analysis views of data analysts and make the analysis results clear at a glance. The design of charts is a big problem, such as the choice of graphics, layout design, color matching and so on. These all need to master certain design principles.

Extended data:

Data analyst? Datician is a kind of data engineer, which refers to a professional who specializes in collecting, sorting out and analyzing industry data of different industries and making industry research, evaluation and prediction based on the data.

This is an era of speaking with data, and it is also an era of competition by data. At present, more than 90% of Fortune 500 companies have established data analysis departments. Well-known companies such as IBM, Microsoft and Google are actively investing in data services, establishing data departments and training data analysis teams. The government and more and more enterprises realize that data and information have become the intellectual assets and resources of enterprises, and the ability of data analysis and processing is becoming more and more dependent on technical means.

Baidu Encyclopedia-Data Analyst