Data analysts belong to the connecting position in the whole enterprise chain, and it is the biggest difficulty for data analysts in their daily work to actively or passively contact many other employees and communicate with employees in different departments and positions.

Take business personnel as an example, if data analysts want to make an analysis report that is really effective to the enterprise, they must contact the front-line business personnel of the enterprise and have a detailed understanding of the business process and the products or services provided by the enterprise.

And many business personnel lack the ability to summarize the narrative, even if the business staff are willing to communicate with you, you must reorganize these piecemeal and unsystematic information into a commonly used index system through guidance, and then analyze it to get effective information.

Enterprise management decision-makers are the biggest challenge for data analysts in communication, because analysis tasks and summary reports are generally directly communicated by data analysts and managers.

The data analyst must combine the whole reporting work with the development of the enterprise at the business level, clarify the specific impact of data analysis on the enterprise's strategic plan, action policy, and development plan, and make decision makers aware of your work through communication.

A mature data analyst must have the ability to quickly understand unfamiliar industries and business knowledge.

For enterprises, the greatest significance of data analysts to them is to be able to analyze the data to get the business situation that is beneficial to the development of the enterprise, which requires that data analysts must be proficient in the business and industry situation of the enterprise. can get relevant information from the data.

There are often novice data analysts who can't wait to carry out actual analysis as soon as they join the enterprise, and the final results are all analytical data that have nothing to do with the actual business of the enterprise.

When reporting data, there is no way to judge the impact on the enterprise business according to the analysis, and it is impossible to put forward an improvement plan for the business based on this information, which leads to dissatisfaction among enterprise management decision-makers.

A truly mature data analyst should be familiar with the specific business of the enterprise, be able to fully understand the enterprise strategy, industry, policy, and ideas, and then combine his own data analysis ability to report the results of data analysis with business logic. to help managers make decisions about the development of the enterprise.

Data analysis, as can be seen from the name, data is the core of the actual work of data analysts.

Being sensitive to data is a requirement for data analysts, and it is also a unique skill developed by data analysts in their daily work. Compared with employees in other positions, it is easier for them to find the hidden rules in data information and judge anomalies in data. This is the ability to be sensitive to data.

I have seen someone say that anyone can do data analysis, so why do they need a data analyst? I think the ability to be sensitive to data is a strong proof.

Because the data is complex and staggered, most people can only analyze it according to a fixed range of normative data, while data analysts can summarize rules from data from various sources and analyze them better. Moreover, the data analyst itself also has professional data statistics and analysis capabilities, which, coupled with the ability to be sensitive to data, can ensure that the data analyst can judge the situation of the enterprise from a more comprehensive and open perspective and get information beneficial to the development of the enterprise.

However, the problem-solving skills that data analysts need to master are much greater, because the job of data analysts is to help companies and businesses find and solve problems through data analysis capabilities.

There are many and complex problems in the development of business and enterprises. for example, sales at a store this month have fallen by half compared with last month, and data analysts have to compare the sales of the previous few months with those of last year to see if it is normal.

After identifying a problem, you need to pull the data from the supply chain, production, operation, etc., to identify the problem, and you may have to explore the market to see if competitive products has opened a new store nearby, or if some big company has moved out.

The possibility of various situations makes it common for data analysts to encounter difficulties in their daily work, and it also allows data analysts to learn to compare data in advance to estimate risks, and to deal with unexpected problems flexibly according to different analytical themes and different coping methods and analytical models.

Data analysts can find enterprise development problems and propose solutions, but it is the management decision-makers who really deal with enterprise problems, which requires data analysts to be proficient in summary and reporting methods to make managers believe in their own plans.

With the advent of informatization and digitalization, more and more enterprises are moving towards the road of digital transformation, and the development prospect of data analysts is becoming more and more broad.