Now, driven by digital transformation, more and more companies realize the charm of big data and continue to invest in this field. Talents related to Python+ big data development are also favored!
Before learning Python: Is this thing really as good as it is said to be?
After learning Python: Oh my god, it smells so good~
It takes others 2 days to process Excel data, but you only spend 1 hour with Python;
Others rely on guts to fish, you rely on Python to automate your office, and fish openly;
When others are looking for resources from one website to another, you can easily find them all with Python;
……
From then on, no matter how difficult the job is, it will no longer be a problem in your eyes~ Promotion and salary increase are all yours! Python is so real!
Python is simple and efficient, which greatly improves the coding speed of programmers and greatly improves the office efficiency of programmers. For example, it can only be understood in 5 or 6 lines of code in other programming languages, and it may be 1-2 lines in Python. can be solved.
Recently, the OpenAI team, which is popular all over the world, was also exposed to use Python as the back-end programming language! With the development of artificial intelligence technology, Python is used more and more frequently. The boss once said that in the entire AI industry, Python is the default development language!
Now, not only Internet companies use the Python programming language, but Python can also be used in the work of professionals.
So some people say that there are only two types of people in this world, one who has learned Python, and the other who is on the way to learn Python.
Python+ has become a sharp tool
to shine in the field of big data
Python has become a sharp tool for people in the workplace to pursue efficiency, because no matter what kind of work, data will be part of the work. Where there is data, there is Python!
We know that with the development of the Internet, online data is increasing in magnitude, and there is a lot of valuable information hidden in huge data, and Python can be used to discover and refine these valuable information, in data mining, data Play a key role in analysis, data visualization, and more!
Now, driven by digital transformation, more and more companies realize the charm of big data and continue to invest in this field. Talents related to Python+ big data development are also favored!
According to the "New Occupation—Analysis Report on the Employment Prosperity of Big Data Engineering and Technical Personnel", the demand for big data talents will reach 2.5 million in 2025!
△ "New Occupation—Analysis Report on Employment Prosperity of Big Data Engineering and Technicians"
Under this gap, the salaries of big data talents have been soaring. Not only can high-paying jobs be found in first-tier cities, but employment in new first-tier cities and provincial capital cities is also very good!
Next, we will specifically talk about the positions that can be occupied by studying big data:
1. Big data development engineer
Develop, build, test and maintain the architecture, responsible for the development and maintenance of the company's big data platform, and responsible for the architecture design and product development of the continuous integration of the big data platform related tool platforms.
2. Data Analyst
Collect, process and perform statistical data analysis; use tools to extract, analyze and present data, and realize the commercial significance of data, which requires business understanding and tool application ability.
3. Data Mining Engineer
Data modeling, machine learning and algorithm implementation; business intelligence, user experience analysis, prediction of churn users, etc.; in addition to strong mathematical and statistical skills, there are also high requirements for algorithm code implementation.
4. Data architect
Requirements analysis, platform selection, technical architecture design, application design and development, testing and deployment; advanced algorithm design and optimization; data-related system design and optimization require platform-level development and architecture design capabilities.
5. Database development
Design, develop and implement database systems based on customer needs, connect databases and database tools through ideal interfaces, optimize performance and efficiency of database systems, etc.
6. Database management
Database design, data migration, database performance management, data security management, troubleshooting issues, data backup, data recovery, etc.
7. Data scientists
Data mining architecture, model standards, data reporting, and data analysis methods; use algorithms and models to improve data processing efficiency, mine data value, and realize the conversion from data to knowledge.
8. Data product manager
Combine data and business to make data products; the platform line provides basic platforms and general data tools, and the business line provides analysis frameworks and data applications that are closer to business.
With the increase in the demand for big data talents, the development space and treatment of the big data industry are getting better and better. Many want to switch to big data. The three main employment directions of big data are big data system R&D talents and big data application development. Talents and big data analysis talents. Regardless of the size of the enterprise, data analysis talents have become a rigid demand, and the advantages of majors are obvious, but related majors and non-graduates can also help their careers by learning and mastering data analysis knowledge while practicing in the workplace.
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.