There are more and more demands for big data, and as long as technology is in hand, there is no need to worry about finding a job.
What language foundation do you need to master to learn big data?
1. Java foundation
More than 90% of big data frameworks use the Java development language, so if you want to learn big data technology, you must first master the basic Java syntax and the relevant knowledge of JavaEE direction.
2. MySQL database
This is one of the knowledge that must be mastered in learning big data. The language of data manipulation is SQL, so the development goal of many tools is to be able to use SQL on Hadoop.
3. Linux system
The framework of big data is installed on the Linux operating system, so proficiency in Linux-related knowledge is also the basic knowledge of big data.
The learning of big data cannot only stay at the theoretical level. The direction of big data is all-round, and the learning of basic language is only a small aspect. After programming is implemented in the end, it is the programming idea. With the guiding ideology, it is easy to learn. Can be much more convenient.
As the tide of the Internet goes to the bottom, and traditional enterprises are undergoing digital transformation one after another, basically every company is considering how to further tap the value of data and improve the operational efficiency of enterprises. In this trend, big data technology is becoming more and more important. Therefore, in the future, big data is one of the necessary skills for our workers.
Friends who pay attention to the IT industry know that the competition of "chasing after me" in programming languages has been going on for a long time.
On the whole, the rankings of major programming languages have not changed much this month, and Python still sits firmly at the top with an unstoppable trend. Currently, Python's market share is 15.49%, an increase of 0.16% from the previous month. It can be said that Python can be seen in almost every programming field.
In recent years, Python has been making great strides, and its popularity is obvious to all. In this regard, TIOBE officials also stated that "Python is very suitable for data mining, artificial intelligence programming, statistical programs, research projects, websites and other fields and scenarios. It is also a place where programmers can quickly learn programming. One of the best languages for
Python has the advantages of being simple, easy to learn, free, open source, portable, extensible, and object-oriented.
Moreover, if you are engaged in Python development, you can choose many positions, such as Python engineer, Python automated testing, data engineer, data mining, artificial intelligence and so on.
From the perspective of salary, according to the data of the third-party platform, the average monthly salary of Python development engineers in Beijing is 23.2K, of which 20K-30K accounts for the largest proportion, and the salary of artificial intelligence, machine learning and other positions is as high as 30K or more.
Therefore, although there are tens of thousands of programming languages, when you are considering which one to learn, you might as well start with the "top" language in the list. The number one Python is a good choice!
Relevant reports show that by 2025, my country's demand for big data-related talents will reach 2.5 million. The development is advancing by leaps and bounds, and the prospects are infinitely broad. If you are also optimistic about this industry, then don't hesitate any longer, because waiting is the reward of waiting; If you act, you will receive preferential treatment!
It can also be seen that in addition to python, java and front-end are also among the best. These are all good choices for employment~
After experiencing the workplace crisis and employment crisis, many talents understand how important it is to have a "settled life" technology. The IT Internet industry has indeed changed the life trajectory of many people.
From the perspective of the industry, entering 2023, the market of leading companies such as Baidu, Alibaba, and Tencent has gradually stepped out of the bottom of the "V" shape and begun to take upward steps. The entire industry is releasing positive signals of recovery. The "2023 New Year Start Employment Report" released by Liepin also shows that talents in the Internet industry are showing a state of "booming supply and demand". The editor dares to predict that the Internet must be one of the hottest industries for job hunting, job hopping, and career change this year.
The Internet industry has the most new jobs:
high salaries and large gaps, naturally become the "salary" choice for professionals in the workplace!
Any learning process requires a scientific and reasonable learning route in order to be able to complete our learning goals in an orderly manner. The content required to learn Python+big data is complex and difficult. We have compiled a comprehensive Python+big data learning roadmap for you to help you clarify your thinking and overcome difficulties!
Detailed introduction to Python+big data learning roadmap
Getting Started with Big Data Development in Phase 1
Pre-study guide: Start with traditional relational databases, master data migration tools, BI data visualization tools, and SQL, and lay a solid foundation for subsequent learning.
1. Big data data development foundation MySQL8.0 from entry to proficiency
MySQL is the entire IT basic course, and SQL runs through the entire IT life. As the saying goes, if SQL is well written, you can find a job easily. This course fully explains MySQL8.0 from zero to advanced level. After studying this course, you can have the SQL level required for basic development.
The core foundation of big data in the second stage
Pre-study guide: learn Linux, Hadoop, Hive, and master the basic technology of big data.
2022 Big Data Hadoop Introductory Tutorial
Hadoop offline is the core and cornerstone of the big data ecosystem, an introduction to the entire big data development, and a course that lays a solid foundation for the later Spark and Flink. After mastering the three parts of the course: Linux, Hadoop, and Hive, you can independently realize the development of visual reports for offline data analysis based on the data warehouse.
The third stage of hundreds of billions of data warehouse technology
Pre-study guide: The course at this stage is driven by real projects, learning offline data warehouse technology.
Data offline data warehouse, enterprise-level online education project practice (complete process of Hive data warehouse project)
This course will establish a group data warehouse, unify the group data center, and centralize the storage and processing of scattered business data; the purpose is from demand research, design, Version control, R&D, testing, and launch, covering the complete process of the project; digging and analyzing massive user behavior data, customizing multi-dimensional data sets, and forming a data mart for use in various scene themes.
The fourth stage PB memory computing
Pre-study guide: Spark has officially adopted Python as the first language on its homepage. In the update of version 3.2, it highlights the built-in bundled Pandas; Spark content.
1. From entry to mastery of python (19 days)
Python basic learning courses, from building the environment. Judgment statements, and then to the basic data types, and then learn and master the functions, familiarize yourself with file operations, initially build an object-oriented programming idea, and finally lead students into the palace of python programming with a case.
2. Python programming advanced from zero to website building
After completing this course, you will master advanced Python syntax, multi-tasking programming, and network programming.
3.spark3.2 from basic to proficient
Spark is the star product of the big data system. It is a high-performance distributed memory iterative computing framework that can handle massive amounts of data. This course is developed based on Python language learning Spark3.2. The explanation of the course focuses on integrating theory with practice, which is efficient, fast, and easy to understand, so that beginners can quickly master it. Let experienced engineers also gain something.
4. Big data Hive+Spark offline data warehouse industrial project actual combat
Through the big data technology architecture, it solves the data storage and analysis, visualization, and personalized recommendation problems in the industrial Internet of Things manufacturing industry. The one-stop manufacturing project is mainly based on the Hive data warehouse layer to store the data of various business indicators, and based on sparkSQL for data analysis. The core business involves operators, call centers, work orders, gas stations, and warehousing materials.