4 thoughts on “What are the job opportunities in the big data industry and what are the job skills recruited?”
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Big data mainly includes the following positions: 1) Data analyst Data Analyst: Refers to the familiarity of related businesses, proficiently build a data analysis framework, master and use related analysis common tools and basic analysis methods For data analysis conclusions to provide guiding opinions on management sales operations. 2) Data architect Data Architect: Guide the entire life cycle of the Hadoop solution, including demand analysis, platform selection, technical architecture design, application design and development, testing and deployment. In -depth grasp of how to write the operation of the Mapree and the management of the operation flow to complete the calculation of the data, and can use the general algorithm provided by Hadoop to be proficient in the components of the entire ecosystem of Hadoop, such as: Yarn, HBase, Hive, Pig and other components, which can realize the realization Development of platform monitoring and auxiliary operation and maintenance systems. 3) Big Data Engineer Big: Collect and process large -scale raw data (including script writing, webpage acquisition, call APIS, write SQL query, etc.); process non -structured data into a form suitable for analysis, and then Analyze; analyze commercial decisions based on the required and project analysis. 4) Data warehouse administrator DATA: specify and implement information management strategies; coordinate and management information management solutions; scope of multiple projects, plans and priority arrangements; all aspects of management warehouses, such as data outsourcing, mobile, mobile, mobile , Quality, design and implementation. rn5)数据库管理员Database manager:提高数据库工具和服务的有效性;确保所有的数据符合法律规定;确保信息得到保护和备份;做定期报告;监控数据库性能;改善使用的技术;建立新Database; detect data entry program; failure exclusion. 6) Commercial intelligence analyst Analyst: For tools, reports, or metadata enhancement for transmission information; conduct or coordinate testing to ensure that the definition of information is consistent with the needs; Potential customers; comprehensively the current business can only support the adoption of action adoption; the commercial intelligence tools, databases, database panels, systems or methods; timely managing user traffic of user traffic. 7) Database developer: Design, development and implementation of database systems based on customer needs; optimize the performance efficiency of the database system; prepare design specifications and functional documents allocated database items; spatial management and capacity planning of the database system ; Establish a database table and dictionary; participate in the design and architecture of the database to support application development projects; implement data backup and regular files; test the database and perform errors; timely solve the database -related problems; formulate security procedures to protect the database to protect the database to protect the database to protect the database to protect the database to protect the database to protect the database It is exempted from unauthorized use; evaluates the existing database, and proposes the implementation efficiency of improvement suggestions; the best practice for development for database design and development activities.
If you want to learn big data development, the first thing is not to find books or video tutorials, but to understand the prospects of the big data industry, to understand what kind of ability to become big data engineers, what skills to master. I have also had such problems before learning big data. As a person who came here, I will talk to you today about the skills that big data talents should have. First of all, we must know that the skills needed for big data development engineers, let’s explain the following:
The ability requirements for big data development talents have skill requirements: 1. Professional Java development language, while being familiar with Python and SCALA development linguistics; 2. Familiar with Spark or Hadoop ecosystem technology, with source code reading and secondary development work experience; proficient in Hadoop ecological and high -performance cache Related various tools, those who have actual combat experience with source code are preferred; 3. Skilled use of SQL, familiar with the principles of databases, familiar with at least one mainstream relationship database; ; Familiar with ETL development, you can be proficient in at least one ETL (Talend, Kettle, OGG, etc.) to transform open source tools; 4. With a clear systematic thinking logic, he has a strong interest in solving the actual problems of the industry, and has good communication with good communication. Coordination and learning ability. The above is the skills that you want to be a big data person So how to have these abilities and how to learn. For most people, only by participating in big data can be systematically learned can it be systematically. Master the above big data skills, so as to be the work of big data engineers.
You can do data visual engineers, data assistant analysts, data modeling engineers, big data analysts, etc. The skills include programming tools such as Python, R, SAS; you need to understand the data warehouse to do some experimental items in Jiudaomen; if you think it is still difficult, then use the most basic learning path to buy mysql relationship directly. Look at the book of the type database, just go to the Internet to find a free MYSQL course to listen;; distributed storage HDOOP needs to be briefly understood; the technology of cloud computing technology can be understood; Everyone understands the chart first, and then study the instrument board, Alibaba Cloud’s Quich Bi and DataV, Baidu’s echarts are good, mainly because the business structure of the display needs to be planned; big data technology: This is relatively difficult. If it is learning mathematics statistics Professional friends are very advantageous. Do n’t worry about other professional friends. After all, you can continue to study after work. Do not do model and algorithm engineer so you only need to use it. It really does n’t work with professional tools for us to use it. Alibaba Cloud ’s machine learning PAN is a tool that can directly produce results; You can go to the Tianchi Contest to see some cases and do training by yourself. If you think it is difficult to persist, you can only go to the class. If you want to be a big data analyst, it will take time to settle it.
Today, I mainly tell you about the employment direction of the big data analysis industry. How to learn big data analysis and how to get started. Many classmates know that this is very hot, but it is not clear what this is doing. Today I will tell you big data analysis engineers. The employment in big data analysis mainly has three major directions: first, data analysis big data talents, second, system R
Big data mainly includes the following positions:
1) Data analyst Data Analyst: Refers to the familiarity of related businesses, proficiently build a data analysis framework, master and use related analysis common tools and basic analysis methods For data analysis conclusions to provide guiding opinions on management sales operations.
2) Data architect Data Architect: Guide the entire life cycle of the Hadoop solution, including demand analysis, platform selection, technical architecture design, application design and development, testing and deployment. In -depth grasp of how to write the operation of the Mapree and the management of the operation flow to complete the calculation of the data, and can use the general algorithm provided by Hadoop to be proficient in the components of the entire ecosystem of Hadoop, such as: Yarn, HBase, Hive, Pig and other components, which can realize the realization Development of platform monitoring and auxiliary operation and maintenance systems.
3) Big Data Engineer Big: Collect and process large -scale raw data (including script writing, webpage acquisition, call APIS, write SQL query, etc.); process non -structured data into a form suitable for analysis, and then Analyze; analyze commercial decisions based on the required and project analysis.
4) Data warehouse administrator DATA: specify and implement information management strategies; coordinate and management information management solutions; scope of multiple projects, plans and priority arrangements; all aspects of management warehouses, such as data outsourcing, mobile, mobile, mobile , Quality, design and implementation. rn5)数据库管理员Database manager:提高数据库工具和服务的有效性;确保所有的数据符合法律规定;确保信息得到保护和备份;做定期报告;监控数据库性能;改善使用的技术;建立新Database; detect data entry program; failure exclusion.
6) Commercial intelligence analyst Analyst: For tools, reports, or metadata enhancement for transmission information; conduct or coordinate testing to ensure that the definition of information is consistent with the needs; Potential customers; comprehensively the current business can only support the adoption of action adoption; the commercial intelligence tools, databases, database panels, systems or methods; timely managing user traffic of user traffic.
7) Database developer: Design, development and implementation of database systems based on customer needs; optimize the performance efficiency of the database system; prepare design specifications and functional documents allocated database items; spatial management and capacity planning of the database system ; Establish a database table and dictionary; participate in the design and architecture of the database to support application development projects; implement data backup and regular files; test the database and perform errors; timely solve the database -related problems; formulate security procedures to protect the database to protect the database to protect the database to protect the database to protect the database to protect the database to protect the database It is exempted from unauthorized use; evaluates the existing database, and proposes the implementation efficiency of improvement suggestions; the best practice for development for database design and development activities.
If you want to learn big data development, the first thing is not to find books or video tutorials, but to understand the prospects of the big data industry, to understand what kind of ability to become big data engineers, what skills to master. I have also had such problems before learning big data. As a person who came here, I will talk to you today about the skills that big data talents should have.
First of all, we must know that the skills needed for big data development engineers, let’s explain the following:
The ability requirements for big data development talents have
skill requirements:
1. Professional Java development language, while being familiar with Python and SCALA development linguistics;
2. Familiar with Spark or Hadoop ecosystem technology, with source code reading and secondary development work experience; proficient in Hadoop ecological and high -performance cache Related various tools, those who have actual combat experience with source code are preferred;
3. Skilled use of SQL, familiar with the principles of databases, familiar with at least one mainstream relationship database; ; Familiar with ETL development, you can be proficient in at least one ETL (Talend, Kettle, OGG, etc.) to transform open source tools;
4. With a clear systematic thinking logic, he has a strong interest in solving the actual problems of the industry, and has good communication with good communication. Coordination and learning ability.
The above is the skills that you want to be a big data person
So how to have these abilities and how to learn. For most people, only by participating in big data can be systematically learned can it be systematically. Master the above big data skills, so as to be the work of big data engineers.
You can do data visual engineers, data assistant analysts, data modeling engineers, big data analysts, etc.
The skills include programming tools such as Python, R, SAS; you need to understand the data warehouse to do some experimental items in Jiudaomen; if you think it is still difficult, then use the most basic learning path to buy mysql relationship directly. Look at the book of the type database, just go to the Internet to find a free MYSQL course to listen;; distributed storage HDOOP needs to be briefly understood; the technology of cloud computing technology can be understood; Everyone understands the chart first, and then study the instrument board, Alibaba Cloud’s Quich Bi and DataV, Baidu’s echarts are good, mainly because the business structure of the display needs to be planned; big data technology: This is relatively difficult. If it is learning mathematics statistics Professional friends are very advantageous. Do n’t worry about other professional friends. After all, you can continue to study after work. Do not do model and algorithm engineer so you only need to use it. It really does n’t work with professional tools for us to use it. Alibaba Cloud ’s machine learning PAN is a tool that can directly produce results; You can go to the Tianchi Contest to see some cases and do training by yourself. If you think it is difficult to persist, you can only go to the class. If you want to be a big data analyst, it will take time to settle it.
Today, I mainly tell you about the employment direction of the big data analysis industry. How to learn big data analysis and how to get started. Many classmates know that this is very hot, but it is not clear what this is doing. Today I will tell you big data analysis engineers.
The employment in big data analysis mainly has three major directions: first, data analysis big data talents, second, system R