What is data analysis? How to do data analysis?

Data analysis is a good career development direction.

1) Simple comments:

Data analysts are internationally renowned for their generous treatment and high status, and are known as the golden profession in China in the 2nd/kloc-0th century. At present, R&D engineer, product manager, human resources, marketing, operation and data analysis are the six most needed positions in the Internet industry in China. Among them, data analysis talents are the most scarce. LinkedIn report shows that the supply index of data analysis talents is the lowest, only 0.05, which is in a state of extreme shortage and is one of the hottest occupations.

Data analyst is a general problem-solving talent, with data cognitive ability, data processing ability, data thinking ability, data presentation ability, data decision-making ability, computer and data analysis information technology, and enterprise actual combat ability. Through big data thinking, it brings value to enterprises from macro planning, micro/market segmentation analysis, scheme implementation and strategic deployment. AI and BI are only part of the skills in the whole process.

2) Highlights of data analysts:

1. The talent gap is very large.

In the era of big data /AI, as long as the company has business decision-making needs, it is inseparable from data analysis.

The employment trend report of big data talents in 20 19 shows that the gap of big data talents in China is as high as 6.5438+0.5 million, most of which are data analysis positions. The strategy of data power makes the demand for data analysis jobs blowout. According to the statistics of IDC, Digital Alliance and other institutions, the number of talents in 20 18 has increased four times compared with that in 20 14, and the talent gap will reach 1.5 million in the next three to five years. At present, there are only about 300,000 big data talents in China! By 2025, China's big data talent gap will reach 2 million.

2. Easy to learn and good to develop

Compared with big data engineers and AI engineers, data analysis is less difficult to learn, and it is easier to develop from data analysis to big data and AI in the future.

3. Employment does not worry about high salary

The data analysis positions of mainstream recruitment websites such as 5 1job are about three to five times that of Java, so there is no worry about employment. There is a lack of talents who use big data thinking to provide data solutions for enterprises. In 20 18, the starting salary of the industry exceeded 200,000/year, which was more than 30% higher than the average salary of the industry! Because of scarcity, it is almost normal for fresh graduates with high salary and zero experience to get the salary of 10K, while the salary of 20k-30k has exceeded 50%.

4. The industry is generally adaptable.

According to the analysis, this is a necessary skill in the workplace that most positions need. All industries need data analysis skills, and financial and e-commerce data analysts are the industries with the greatest demand.

5. Long career life

Data analyst is one of the few jobs that won't be unemployed, and the older you get, the better.

Ma Yun once said: "In the next 30 years, data will replace oil and become the most powerful energy." At present, nearly 50% of the positions need to have the ability of data analysis, such as product manager, new media operation, event planning, user research and other positions of internet companies, and the recruitment conditions of "having the ability of data analysis" are also given. Mastering data analysis ability = 50% more job opportunities!

6. University majors have a wide range of adaptation.

Students majoring in computer, information, mathematics, statistics, e-commerce, economy, finance, statistics, investment, finance and enterprise management, as well as fresh graduates, can engage in data analysis.

2) industry positioning and application:

1. Governments and institutions:

Leaders of government agencies and relevant employees responsible for project review, approval, investment promotion, project evaluation and decision-making.

2. Financial institutions: staff in financial institutions and management consulting companies who manage venture capital, financial product research and development, credit and other related projects.

3. Business units: staff in related positions such as attracting investment, expanding reproduction, financial audit, market analysis and data mining.

4. Firms: data analysts, accounting firms, asset appraisal firms, tax agents and law firms.

5. Universities and vocational and technical colleges: students majoring in computer, mathematical statistics, economics, finance, statistics, investment, finance and management.

6. Others: entrepreneurs and people with lofty ideals who want to develop in investment finance, capital operation, real estate and enterprise management.

3) Work content of data analyst

1. Support product improvement and new mode exploration through data analysis;

2. Build a data evaluation system and a business data analysis system to help determine various business data indicators;

3. Responsible for user behavior data analysis, and promote product improvement and operation adjustment through monitoring and analysis;

4. Responsible for building user data model, mining user attributes and user preferences, and providing support for personalized product recommendation;

5. Build a user behavior evaluation system for products/operations/activities, and make suggestions for products/operations/markets through data analysis;

6. Through the mining and analysis of massive data, a report is formed and submitted to the decision-making level to support strategic planning.

4) Data analysis of career development direction

6) Salary analysis: