Zhihu Gaozan: what ability is important, but most people don't have it?

You know, there's a hot question : Which abilities are important , But most people don't ？

This topic has attracted close attention 20 ten thousand , The number of visitors is close to 4 Ten million , Two things that surprised me most , First, we are eager to build scarce capacity ; second , The best answer , The answer is that the Lord really uses important abilities that most people don't have , Success gains 2w+ Like , Top of the list .

Answer: the content of the Lord is not a high-level and profound skill explanation , But to find another way , Use your own data analysis thinking 、 Skill , All the answers to this topic have been sorted out 、 Sort , Become the driest item on this topic 、 Live map , Harvest a piece of praise .

You see , It's just a change of mind 、 Application of skills , It has unexpected effects ~

This is the difference between using data to speak , In most business scenarios , The data are more convincing .

actually , With the big data era , This ability is becoming more and more important , If you look carefully, you will find , At present, many high paying jobs have secretly added a competency requirement , That's it ：

> Data analysis

Data analysis is not an emerging position , But with the gradual implementation of the concept of big data , The value of data is gradually valued by enterprises , As a result, the value of data analysts has doubled .

near 50% Your position requires 「 Data analysis 」 Ability , Now almost most popular jobs are in recruitment JD in , give “ Have the ability of data analysis ” Such recruitment conditions . Coverage consulting 、 An accounting firm 、 The consumer 、 Finance 、 Internet and other popular industries .

and , Data analysis jobs usually have a higher starting salary . New to the workplace with zero experience Fresh graduates get 10K Salaries have become almost the norm , and 20k-30k There are also a lot of people who pay .

without doubt , Data analysis capability has become the most potential at present , Most likely " money " One of my abilities ！

Career prospects for data analysts ？

not long ago , The school of economics and management of Tsinghua University issued 《 The digital transformation of China's economy ： Talent and employment 》 The report of , According to the report , At present, the talent gap in the field of big data in China is as high as 150 ten thousand , To 2025 The years will reach 200 ten thousand .

This report is for the country , It's planning ahead 、 Reference to advance layout ; For enterprises , It's a sign of cutting into the next track ; And for ordinary people , Is an opportunity , One who can get a quick promotion , Even the opportunity to achieve wealth and freedom .

In the U.S. , The average annual salary of big data analysts is as high as 17.5 Thousands of dollars , And the top Internet companies in China , The salary of big data analysts may be higher than other positions at the same level 20% to 30%, And quite by the enterprise attention .

Domestic recruitment online , We analyzed the data collected by reptiles and found that , Nationwide 29 Enterprises in cities have a talent demand for data analyst positions , Nearly half of the demand is generated in Beijing , The demand ranks first in China . In front 5 The difference is ： Beijing 、 Shanghai 、 Shenzhen 、 Hangzhou 、 Guangzhou .

The profession of data analysis is largely concentrated in the four first tier cities of Beijing, Shanghai, Guangzhou and Shenzhen , And Hangzhou, the gathering place of Internet and e-commerce enterprises .

A conclusion can be drawn from the above data ： Data Analyst , A large number of job opportunities are concentrated in Beijing, Shanghai, Guangzhou, Shenzhen and Hangzhou , Students who are looking forward to developing in this direction should try more in these cities .

Of course , On the other hand , These cities also have a large number of talents in various industries , The competitive pressure must also be great .

Career direction and growth path ？

Of course , Before formally entering an industry , Besides interest and personality , It is more necessary to examine the career development direction and growth route .

such as ： What is the career development and growth path of data analysis ？

Positions in the data analysis industry , It can be roughly divided into four directions ： Data analysis 、 data mining 、 Data development 、 Data products .

1) Data Analyst

Engaged in data collection 、 Arrangement 、 analysis , Find the problem , To analyze problems , Come to the conclusion , Provide data support for the decision-making level of the company , Prefer business .

2) Data mining engineer / Algorithm engineer

Use model training data , Mining rules from massive data , Predict or classify objects , The main bias is programming and algorithms , The demand for statistical theory knowledge is on the high side .

3) Data Development Engineer

Design 、 Build and maintain infrastructure , To provide data collection 、 Storage 、 Handle 、 Computing and other platforms . Partial code development , Need to make up for in code capability , But compared with the programmers of pure technology stack, they need some business logic .

4) Data product manager

It is mainly responsible for refining requirements based on data 、 Design 、 planning 、 The project is scheduled until the project is completed , And later product improvement and optimization .

But you can't start with these positions , Data analysts also start from the basic position , Slowly progressive .

What to learn ？

There are three main parts to learn about data analysis ： Tools 、 theory 、 Business

Tools ：
It mainly refers to the tools used for data analysis , It mainly includes esp Three piece set , That is to say Excel,Sql,Python. There are also some visual tools （ such as tableau,power bi etc. ）

theory ：
It includes two aspects
a. Probability theory and mathematical statistics 、 Mathematical knowledge and other data analysis framework 、 methodology 、 Model, etc
b. The learning and training of data analysis thinking depends on actual business experience , Therefore, numerical thinking is more difficult to learn than skills .

Recommend learning methods ： Combination of learning and Practice , Do more , More practice . Many knowledge points are interconnected , So when learning new skills, you should review the old knowledge points .

Business ：

The businesses of different sub sectors are very different , There is no real business scenario , I can't improve my business very well . It is recommended to understand the common business indicators of the target industry in the early stage .

The salary of data analysts is so " beautiful ", Is work very tiring ？

Become a qualified data analyst , It's not that simple , The career of data analyst is definitely promising , However , This also shows that this is not an easy job , The employment threshold is not low .

Data analysts need to store a lot of knowledge , The need for information 、 Data sensitive , Have the comprehensive ability of data analysis or data mining , The responsibility is also very important .

Does this mean that data analysts are tired , You need to work overtime often ？NO！

Data analyst this is just a profession , Whether the work is tiring or not has a lot to do with the company industry , Of course, it has something to do with your proficiency , At the beginning of this career, students need to keep learning , At this time, it will be relatively tired , When you have a certain foundation and accumulated experience, it will be much better .

As the saying goes “ Eat the bitter in the bitter , rise to the top ”, To be a good data analyst , Win a high salary and reach the peak of your life , perseverance prevails ！

Finally, to borrow a famous quote from Lei Jun, Xiaomi's boss ： When the wind comes , Pigs can fly . But the premise is , We also have to stand in this air outlet first .

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