What is Big Data Technology? What is the main learning of big data technology?

Big data is to sort out and summarize various data between an enterprise and a public institution or between multiple enterprises and institutions, and then unify them into a data chain.

The computer school has this major, and you can just go to the audition to understand it.

At the age of 16, it is almost the age of graduating from junior high school, it is generally not recommended to go directly to work, the age is young, easy to be bullied, you can go to a regular place to learn technology, boys can learn Chinese food, Western food, girls can learn Western pastry, now kindergarten teachers are not bad, there is a technology in hand, or can.

1. Data collection2. Intelligent analysis of big data.

3. Big data information mining.

What is the employment direction of big data technology?

1.Internet e-commerce direction.

As the hottest outlet at present, Internet e-commerce is the place where the Internet field is used in the most practice, and it is also the part with the largest demand for talents. Graduates majoring in big data technology and application can be engaged in Internet e-commerce operation and maintenance, daily management, consumer big data analysis, financial data risk control management and other related technical work. At present, from the head e-commerce platforms that have been listed to the community e-commerce, the gap of these technical talents is relatively large.

2.Retail Finance.

Although retail finance and Internet e-commerce both belong to the field of consumption, specifically, the scope of retail e-commerce is smaller than that of Internet e-commerce, and it is more necessary to accurately connect with consumer groups and consumer groups' hobbies, incomes and other characteristics than Internet e-commerce. Graduates of Big Data Technology and Application can work in computer-based, etc. development and other work.

It is suitable for undertaking related technical services in retail financial enterprises, and can also be engaged in computer application work in the IT field.

Need to learn: Programming languages, Linux, SQL, Hadoop, Spark, Machine Learning. Employment direction:

ETL R&D, Hadoop development, visualization tool development, information architecture development, data warehouse research, OLAP development, data science research, data analysis, enterprise data management, data security research. No matter what era it is, people like to make choices in groups when they understand and learn about certain emerging things, such as which industry has a high salary, and what technology is good for employment. Nowadays, with the advent of the 5G era, big data technology and artificial intelligence are gradually becoming the mainstream technology of modern society, so there will be more and more people who want to understand and learn big data technology, one is to follow the pace of the times and seek development, and the other is to seek development for their own interests.

Although the difficulty of learning big data is not very large, it still takes a lot of effort to learn this technology thoroughly, because the big data major needs to learn relatively more knowledge points, and needs a comprehensive and systematic learning, the learning of any technical knowledge is from shallow to deep, and friends who choose big data majors can only get better employment opportunities in the fierce employment environment if they fully learn and master this technology. Big data is characterized by its ability to respond flexibly, quickly and efficiently to various market needs. Big data has a wide range of audiences, not only improving people's social activities and lifestyles, but also bringing more business opportunities and business value to enterprises by using big data technology.

Big data is not only closely related to the IT industry, but many industries have begun to deploy big data operations, such as finance, medical care, etc. Based on big data technology, Shaking Big Data has developed its own big data digital intelligence investment promotion system, creating a precise investment promotion service cloud platform for industrial investment, which greatly improves the dilemma of investment attraction in the industrial park at this stage.

The first is the foundation phase. This stage includes: the principle of relational database, the principle and application of Linux operating system.

After mastering these basic knowledge, advanced courses will be arranged for these basic courses, namely: data structures and algorithms, MySQL database application and development, and shell script programming. After mastering these contents, the basic learning stage of big data is considered to be completed.

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Next is the second stage of big data professional learning: big data theory and core technology. The second stage is also divided into two parts: basic and advanced, first understand the basic knowledge, and then further understand and practice the knowledge content.

The basic part includes: the principle and application of distributed storage technology, distributed computing technology, Hadoop cluster construction, operation and maintenance; Advanced content includes: HDFS high reliability, ZooKeeper, CDH, Shauffle, Hadoop source code analysis, Hive, HBase, MongoDB, and Hadoop project practice.

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After completing this part of the study, you have mastered most of the knowledge of big data and have certain project experience. However, in order to have a better development in the big data major, the knowledge learned can be more widely applied to various positions related to big data, and there is a longer development prospect. _x000d_

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The third stage is called data analysis and mining and advanced processing of massive data. The basic parts are: Python language, machine learning algorithms, Flume+Kafka; The advanced parts are:

Machine learning algorithm library application, real-time analysis and computing framework, Spark technology, Python high-level language application, distributed crawler and anti-crawler technology, real-time analysis project practice, machine learning algorithm project practice.

If you want to know more about big data learning, you can consult the CDA certification center. The CDA industry standard is jointly formulated by industry experts, scholars and well-known enterprises in the field of data on an international scale and revised and updated every year, ensuring that the standard is public, authoritative and cutting-edge. Those who pass the CDA certification exam can obtain the CDA certification certificate in both Chinese and English.

Mainly computer and data analysis, the use of computer computing power, through certain algorithms, probability theory and statistical analysis theory, based on a large amount of data, summarize some laws, and apply these results to the actual environment.

The contents of the big data major are: 1. JA-VA; 2. Big data foundation; 3. Hadoop system; 4、scala；5、kafka；6、spark；7、python；8、mysql。The big data major is divided into two types: big data development, data analysis and mining.

There are two types of big data majors, one is big data development, and the other is data analysis and mining.

1. Big data development: JA-VA, big data foundation, Hadoop system, Scala, Kafka, Spark, etc.;

2. Data analysis and mining: Python, relational database MySQL, document database MongoDB, in-memory database Redis, data processing, data analysis, etc.

The content varies from school to school, but it's pretty much the same. It's all data analysis and mining.

Big data technology is a technical system involving big data collection, storage, processing, analysis, application and other fields. Therefore, the subject areas involved are relatively extensive, and the main learning contents include: 1

Database System: Learn basic database theory, structure, and operations, such as relational database models, data model design, SQL statements, etc. 2.

Data structures and algorithms: Learn basic data structures and algorithms, such as trees, graphs, sorting algorithms, etc., which will serve as an important foundation for processing big data. 3.

Data Mining: Learn the real-world applications and techniques of data mining, and master the use of various data mining algorithms and tools. 4.

Machine learning: Learn the principles, methods, and algorithms of machine learning, such as classification, clustering, regression analysis, and object guessing neural networks, and be able to apply them to the analysis and mining of big data. 5.

Data Visualization: Learn the basic theories and methods of data visualization, such as diagram design, visual programming, interactive design, etc., so as to better present the analysis results to relevant personnel. 6.

Big data technologies and tools: Learn various big data technologies and tools, such as Hadoop, Spark, NoSQL databases, etc., understand their basic principles and usage methods, and conduct big data processing and analysis. 7.

Big Data Applications: Learn practical cases of big data applications in various industries, and also need to understand some practical skills such as enterprise demand analysis, architecture design, and implementation plans.

Summary. Big data technology is an interdisciplinary discipline: statistics, mathematics, and computer science are the three supporting disciplines; Biology, medicine, environmental science, economics, sociology, and management are applied and expanded disciplines.

In addition, students need to learn data collection, analysis, and processing software, mathematical modeling software, and computer programming languages.

Big data technology is an interdisciplinary discipline: statistics, mathematics, and computer science are the three supporting disciplines; Biology, medicine, environmental science, economics, sociology, and management are applied and expanded disciplines. In addition to this, you also need to learn data collection, analysis, processing soft front components, mathematical modeling software and computer programming languages, etc.

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Summary. 1. Collect data and screen the data effectively. 2. Intelligently analyze data, extract useful information, and transform it into practice.

3. Information mining, the operation of knowledge discovery within the database. Big data technology is a new technology that has emerged with the continuous development of information technology, combined with advanced artificial intelligence and the Internet, which can well assist people in analyzing problems, especially in processing data and screening information, big data has very strong advantages. In the early stage, data collection is carried out to understand the development status of the industry, effectively screen the data, and dig out the data information with practical application value hidden in a large number of data information.

1. Collect data and effectively screen the data of the group. 2. Intelligently analyze data, extract useful information, and transform it into practice. 3. Information mining, the operation of knowledge discovery within the database.

Big data technology is a new technology that is accompanied by the continuous development of information technology, combined with advanced artificial intelligence and interconnection, which can well assist people in the analysis of problems, especially in processing data and screening information, big data has very strong advantages. In the early stage, data collection is carried out to understand the development status of the industry, effectively screen the data, and dig out the data information with practical application value hidden in a large number of data information.

What does big data do to learn.