In 2019, Siemens kicked off the Internet winter with 10,400 layoffs.
Followed by Didi’s huge loss of 10.9 billion and announcing 2,000 layoffs, the news was swiped in the circle of friends.
Not long after, Jingdong announced that it would eliminate 10% of the last employees. Not only major Internet companies, but also large foreign companies such as GM, Ford, Bayer, and IKEA, have also reported layoffs...
Under such a background, in order to protect their jobs, everyone is in danger. The so-called stable work has long ceased to exist.
However, under the wave of layoffs all over the world, only the emerging industry of "data analysis" has not been affected. On the contrary, in the cold wave, the torrent has been advancing bravely, and the salary has increased.
Well-known Internet companies have offered 35K-70K annual salary to introduce data analysis talents, but the supply is still in short supply.
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What is the magic of data analysts?
Nowadays, with the development of AI technology and the popularity of emerging technologies such as big data, cloud computing, and artificial intelligence, the term "data" has become the darling of the industry.
And the amount of data has increased in recent years. Obtaining commercial value from data and realizing the transformation of data assets have now become the key path for every enterprise's data transformation.
If you are currently anxious about your future. Or if you think you can’t avoid three to five 10% eliminations at the end, you might as well take a look at your career. Sometimes it’s a smart choice to change your path.
The 5G era has arrived, and the amount of Internet data has exploded. It is expected that by 2020, the number of data bytes on the Internet will reach 40 times that of observable universe stars!
The amazing amount of data per minute enters the application with the big data analysis
During the outbreak period, the demand for employment of enterprises will also explode! Currently engaged in big data analysis related work, the starting salary is at least 15K, and the annual salary of those with experience is as high as 500,000-700,000, which is extremely short of people!
In the wave of big data and artificial intelligence, as long as the company has business decision-making needs, it is indispensable Open the "tool" of data analysis. If you don't understand data, popular positions will be missed to a large extent, and full-time data analysts are also "highly paid because of scarcity."
According to the "Big Data Talent Report" released by Datalink Search, my country's big data talents are currently only 460,000, and the big data talent gap will be as large as 1,500,000 in the next 3-5 years. Therefore, the treatment of data talents in the job market is hateful.
Where does big data analysis start?
Why are these big data analysis jobs so popular?
What kind of technical storage is needed for big data analysis?Ready?
How can I quickly get started with big data analysis?
The editor has researched many times from the recruitment website and compiled a map of the necessary skills for big data analysis engineers to provide some learning lessons and references for those who want to transform or upgrade.
Many people want to enter the field of big data analysis. In fact, the core of big data analysis lies in data The collection, storage, processing, analysis and mining.
And mastering these two technologies also requires Python programming and statistics foundation and database-related knowledge as support. Although it may seem difficult, it is not terrible.
The editor compiled a set of "Statistics + Database + Python Series Introductory Video Tutorials" carefully crafted by the industry's senior big data analysis experts, and gathered years of practical experience & cutting-edge big data analysis project cases. Artifact!
A series of introductory tutorials for big data analysis
The first stage: essential skills for big data analysis-basic statistics
01. The nature of the sample
02. Descriptive analysis
03. Visual analysis
04. Relevant and independent analysis 1
05. Relevant and independent analysis 2
The second stage: Essential skills for big data analysis-database foundation
01. Introduction to the database
02. Simple database query
03. Database group query
04. Database related query
05. mysql execution principle
06. mysql classic interview-rank conversion problem
07. Storage engine, index, sql optimization, slow query
The third stage: Big data analysis essential skills-Python programming
01. Python entry program
02. Python variable naming
03. Operation operator
04. Process control (if)
05. Process control (while)
06. Process control (for)
07. Summary of all knowledge of the function
08. Modules and guide packages
09. The most basic theory of crawlers
10. Use regular to capture famous quote data
11. Use BeautifulSoup to capture famous quotes
12. Use xpath to capture famous quotes
Additional welfare
In addition to the above heavy benefits, an additional 12G big data analysis will be given Professional materials, including a large number of big data analysis and Python professional books PDF version, practice questions, industry reports, interview books, knowledge graphs, learning materials, practical cases, etc., everything is too much, the editor will not take screenshots to show ~
All the above benefits will be given to fans for free
How to get this set of tutorial materials?
Repost this article, follow and privately write the keyword "learning" to get it for free immediately
The following is the python learning route and video. It is divided into 7 major stages.
Now share with you for free! Get it at the end of the article! ! !
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- Design pattern and exception handling
- tank battle
- core programming
- jquery animation special effects
- Ajax asynchronous network request
- Django-blog project
- Django-mall project
- regular expressions
- Python crawler basics
- Python crawler Scrapy framework
The first stage, python development foundation and core features
1. Variables and operators
2. Branches and loops
String
4. List and nested list
5. Dictionary and project exercise
6. Use of function
7. Recursion and file handling
8. File
9. Object-oriented
10. Design patterns and exception handling
11. Exceptions and the use of modules
12. Tank battle
13. Core programming
14. Advanced features
15. Memory management
The second stage, database and linux basics
1. Concurrent programming
2. Network communication
3.MySQL
4.Linux
5. Regular expressions
The third stage, web front-end development foundation
2.css style
3.css floating and positioning
4.js basic
5.js objects and functions
6.js timers and DOM
7.jsevent response
8. Use jquery
9.jquery animation effects
10.Ajax asynchronous network request
Fourth stage, Python web framework stage
1.Django-Git version control
2.Django-blog project
3.Django-mall project
4.Django model layer
5.Django entry
6.Django template layer
7.Django view layer
8.Tornado framework
The fifth stage, Python crawler actual development
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1.Python crawler basics
2.Python crawler Scrapy framework
The above python self-study tutorial editor has been packaged and prepared for everyone, I hope it will help you who are learning!
