4 thoughts on “What is the career prospect of data analysts? What are the main industries? What skills do you need?”
Pam
Data analysis should learn programming tools such as Python, R, SAS; you need to understand the data warehouse to do some experimental projects in Jiudaomen; if you think it is still difficult, then use the most basic learning path to buy the book of MySQL relational database. Look, go to the Internet to find a free MYSQL course to listen; distributed storage HDOOP requires a simple understanding; cloud computing technology can be understood; data visualization is not difficult. Then study the instrument board, Alibaba Cloud’s Quich Bi and DataV, Baidu’s echarts are good, mainly because the business structure displayed is planned; big data technology: This is relatively difficult. It is very advantageous. You don’t have to worry about other majors. After all, you can continue to study after work. More use in work is clustering, association, decision tree, linear regression, etc. The algorithm engineer only needs to use it. It really doesn’t work for professional tools for us. Alibaba Cloud’s machine learning PAN is a tool that can directly produce results. You can go to the official website of Jiudao Men’s business data analysis training website 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, or let the teacher take you. After taking it for half a year, this set is basically skilled.
The main task of data analysts is to extract valuable information from the company’s existing data. This value information must be developed in accordance with the company’s industry. Come to pay more attention to data analysis, but there are very few experience data analysts, so the talent gap is still very large The knowledge that needs to be mastered: 1. Data analysis theoretical basics-statistical, probability theory r . Data analysis tools-EXCEL, SPSS, SAS/R 3. The understanding of the company’s business (depending on the company)
The data analyst refers to different industries, specializing Professionals engaged in industry data collection, sorting, analysis, and making industry research, evaluation and prediction based on data.
From the perspective of position salary, the high salaries of the data analysis industry are mainly distributed in the Yangtze River Delta, the Pearl River Delta and the Beijing -Tianjin region. The salary of Beijing, Shanghai and Shenzhen ranks first -party array, with an average salary of 10k ; Hangzhou, Ningbo and Guangzhou are ranked second -square, with an average salary of 9K ; other central cities in the coast and inland regions, such as Nanjing, Chongqing, and Suzhou, Wuxi, etc. are located in the third party, with an average salary of about 8K. It’s positions, Beijing, Shanghai, Shenzhen, and Guangzhou are ranked first, with a number of positions in 30,000 . Hangzhou, Chengdu, Nanjing and Tianjin are ranked second. Wuhan, Xi’an, Zhengzhou and other regional centers or provincial capital cities have relatively high demand for data analysis positions, and the number of positions is 10000 . If in the perspective of industry needs, Internet finance, O2O, data services, education, e -commerce, cultural and entertainment areas have greater demand for data analysts than other industries. While in enterprises or society, data has begun to play an increasingly important “character”. In this general trend, data analysis thinking is not just the “professional” of data analysts, including the front -end positions such as sales, marketing, operation, planning, products, etc. need to help their work through data analysis, and even even the data analysis, even The background finance, legal affairs, personnel, etc. also began to improve efficiency through data analysis. It can be said that if you work among companies, you will start to deal with data more and more in the future. At this time, data analysis has become a necessary condition for work. The example here: The products now, because the sales channels begin to be network, so basically each product is in the division of customer base, competing product analysis, sales prediction, etc. Modeling and analysis must be based on data. In the past, as long as you write a product analysis book, draw the prototype of the product, the “good day” of doing product interaction has passed. Let’s put it this way, in more and more companies, if the product cannot get data to support its work, it is basically the support of no resources. It again, the operation is not separated from the data. To do an event, how to divide the target group, what are the solutions of different groups, and how much the output is expected to be invested, these require data support; as small as a marketing talk, it also needs to cut the crowd to make a comparison experiment to decide. It can be said that there are fewer and fewer operations that do not rely on data analysis. The example of the background department finally gives. When doing human planning, the current HR is from personnel structure analysis to configuration strategy analysis to cost analysis, no matter which item needs to be used. In addition to the company’s human data, business data also needs to compete for the company’s data and even the entire industry data. Through the analysis of a large amount of data, the company’s human resources strategy can be more accurate.
The role of data analysts . More and more companies will choose professionals who have project data analysts to make a scientific and reasonable analysis of their projects in order to correctly decide the project; more and more venture capital investment; more and more venture capital investment The project data analysis report issued by the project data analyst as an important basis for whether the project is feasible and whether it is worth investing in it; more and more enterprises take the project data analyst course as a high management and decision -making layer training plan. Important content; more and more people with aspiring use the training content of project data analysts as the necessary knowledge system in their career development. Im work responsibilities of data analysts in this paragraph Data analysts refer to majors in different industries, specializing in industry data collection, finishing, analysis, and based on data to make industry research, evaluation and prediction. personnel. The Internet itself has the characteristics of digitalization and interactivity, which has brought revolutionary breakthroughs to data collection, sorting, and research. In the past, data analysts in the “Atomic World” spent higher costs (funds, resources, and time) to obtain support research and analysis data. The richness, comprehensiveness, continuity and timeliness of the data were much worse than the Internet age. In the “Atomic World”, sampling surveys are the most commonly used data acquisition methods. The main reason is that the cost of a large -scale census is too high -the most typical application is TV ratings. In the Internet era, research on the Internet industry can achieve low -cost and high -efficiency full -sample data collection in local (such as a cluster of a certain website or similar websites). Similarly, many data in the “Atomic World” are not continuous, while data in the Internet world may be continuously updated, even real -time -the most typical application is the statistics and analysis of the full samples of the website, all -weather data statistics and analysis. Compared with traditional data analysts, data analysts in the Internet era are not data lack of data, but excess data. Therefore, data analysts in the Internet era must learn to use technical means for efficient data processing. More importantly, data analysts in the Internet era must continue to innovate and break through in data research methodology. For example, combined with the traditional consumer psychology theory, we will build a wealth of Internet information consumption behavior models. As far as the industry is concerned, the value of data analysts is similar to this. As far as the press and publication industry is concerned, whether in any era, whether media operators can accurately, detailed and timely understanding the situation and change trends are the key to the success of the media. Data analysts are very promising in this regard. In addition, for the content industries such as press and publication, more importantly, data analysts can use the function of content consumer data analysis, which is a key function that supports press and publication agencies to improve customer service. For example, collecting content consumer information, forming content consumer information databases, and maintaining information and maintenance of products and services based on the database information and content of the content of the database, the update and maintenance of the database. As a result, the data provided by data analysts will also become an important basis for customized products and personalized services: with the help of advanced database technology, in -depth mining and multiple use of content resources, provide personal preference content services, or use digital printing with digital printing And publishing technology, realize the production of products on demand and delivery and printing. In the requirements of data analysts of this paragraph skill requirements 1. Undergraduate or above, mathematical statistics or data mining professional direction 2. Familiar with data analysis and data mining theory 3. Proficient in various use of various use Mathematical statistics, data analysis, data mining tool software 4. Those with e -mail work experience is preferred 5. Familiar with Internet application technology knowledge and network knowledge, understand the Internet and mail other requirements good communication ability , Text language expression ability, good logical analysis ability; have independent product planning and development capabilities, project management, business communication ability; strong responsibility, open personality, good communication skills; good at cooperation, good team cooperation Spirit; be able to carry out work under pressure; good at learning
Data analysis should learn programming tools such as Python, R, SAS; you need to understand the data warehouse to do some experimental projects in Jiudaomen; if you think it is still difficult, then use the most basic learning path to buy the book of MySQL relational database. Look, go to the Internet to find a free MYSQL course to listen; distributed storage HDOOP requires a simple understanding; cloud computing technology can be understood; data visualization is not difficult. Then study the instrument board, Alibaba Cloud’s Quich Bi and DataV, Baidu’s echarts are good, mainly because the business structure displayed is planned; big data technology: This is relatively difficult. It is very advantageous. You don’t have to worry about other majors. After all, you can continue to study after work. More use in work is clustering, association, decision tree, linear regression, etc. The algorithm engineer only needs to use it. It really doesn’t work for professional tools for us. Alibaba Cloud’s machine learning PAN is a tool that can directly produce results. You can go to the official website of Jiudao Men’s business data analysis training website 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, or let the teacher take you. After taking it for half a year, this set is basically skilled.
The main task of data analysts is to extract valuable information from the company’s existing data. This value information must be developed in accordance with the company’s industry. Come to pay more attention to data analysis, but there are very few experience data analysts, so the talent gap is still very large
The knowledge that needs to be mastered:
1. Data analysis theoretical basics-statistical, probability theory r
. Data analysis tools-EXCEL, SPSS, SAS/R
3. The understanding of the company’s business (depending on the company)
The data analyst refers to different industries, specializing Professionals engaged in industry data collection, sorting, analysis, and making industry research, evaluation and prediction based on data.
From the perspective of position salary, the high salaries of the data analysis industry are mainly distributed in the Yangtze River Delta, the Pearl River Delta and the Beijing -Tianjin region. The salary of Beijing, Shanghai and Shenzhen ranks first -party array, with an average salary of 10k ; Hangzhou, Ningbo and Guangzhou are ranked second -square, with an average salary of 9K ; other central cities in the coast and inland regions, such as Nanjing, Chongqing, and Suzhou, Wuxi, etc. are located in the third party, with an average salary of about 8K.
It’s positions, Beijing, Shanghai, Shenzhen, and Guangzhou are ranked first, with a number of positions in 30,000 . Hangzhou, Chengdu, Nanjing and Tianjin are ranked second. Wuhan, Xi’an, Zhengzhou and other regional centers or provincial capital cities have relatively high demand for data analysis positions, and the number of positions is 10000 .
If in the perspective of industry needs, Internet finance, O2O, data services, education, e -commerce, cultural and entertainment areas have greater demand for data analysts than other industries.
While in enterprises or society, data has begun to play an increasingly important “character”. In this general trend, data analysis thinking is not just the “professional” of data analysts, including the front -end positions such as sales, marketing, operation, planning, products, etc. need to help their work through data analysis, and even even the data analysis, even The background finance, legal affairs, personnel, etc. also began to improve efficiency through data analysis. It can be said that if you work among companies, you will start to deal with data more and more in the future. At this time, data analysis has become a necessary condition for work.
The example here:
The products now, because the sales channels begin to be network, so basically each product is in the division of customer base, competing product analysis, sales prediction, etc. Modeling and analysis must be based on data. In the past, as long as you write a product analysis book, draw the prototype of the product, the “good day” of doing product interaction has passed. Let’s put it this way, in more and more companies, if the product cannot get data to support its work, it is basically the support of no resources.
It again, the operation is not separated from the data. To do an event, how to divide the target group, what are the solutions of different groups, and how much the output is expected to be invested, these require data support; as small as a marketing talk, it also needs to cut the crowd to make a comparison experiment to decide. It can be said that there are fewer and fewer operations that do not rely on data analysis.
The example of the background department finally gives. When doing human planning, the current HR is from personnel structure analysis to configuration strategy analysis to cost analysis, no matter which item needs to be used. In addition to the company’s human data, business data also needs to compete for the company’s data and even the entire industry data. Through the analysis of a large amount of data, the company’s human resources strategy can be more accurate.
The role of data analysts
. More and more companies will choose professionals who have project data analysts to make a scientific and reasonable analysis of their projects in order to correctly decide the project; more and more venture capital investment; more and more venture capital investment The project data analysis report issued by the project data analyst as an important basis for whether the project is feasible and whether it is worth investing in it; more and more enterprises take the project data analyst course as a high management and decision -making layer training plan. Important content; more and more people with aspiring use the training content of project data analysts as the necessary knowledge system in their career development.
Im work responsibilities of data analysts in this paragraph
Data analysts refer to majors in different industries, specializing in industry data collection, finishing, analysis, and based on data to make industry research, evaluation and prediction. personnel. The Internet itself has the characteristics of digitalization and interactivity, which has brought revolutionary breakthroughs to data collection, sorting, and research. In the past, data analysts in the “Atomic World” spent higher costs (funds, resources, and time) to obtain support research and analysis data. The richness, comprehensiveness, continuity and timeliness of the data were much worse than the Internet age. In the “Atomic World”, sampling surveys are the most commonly used data acquisition methods. The main reason is that the cost of a large -scale census is too high -the most typical application is TV ratings. In the Internet era, research on the Internet industry can achieve low -cost and high -efficiency full -sample data collection in local (such as a cluster of a certain website or similar websites). Similarly, many data in the “Atomic World” are not continuous, while data in the Internet world may be continuously updated, even real -time -the most typical application is the statistics and analysis of the full samples of the website, all -weather data statistics and analysis. Compared with traditional data analysts, data analysts in the Internet era are not data lack of data, but excess data. Therefore, data analysts in the Internet era must learn to use technical means for efficient data processing. More importantly, data analysts in the Internet era must continue to innovate and break through in data research methodology. For example, combined with the traditional consumer psychology theory, we will build a wealth of Internet information consumption behavior models. As far as the industry is concerned, the value of data analysts is similar to this. As far as the press and publication industry is concerned, whether in any era, whether media operators can accurately, detailed and timely understanding the situation and change trends are the key to the success of the media. Data analysts are very promising in this regard. In addition, for the content industries such as press and publication, more importantly, data analysts can use the function of content consumer data analysis, which is a key function that supports press and publication agencies to improve customer service. For example, collecting content consumer information, forming content consumer information databases, and maintaining information and maintenance of products and services based on the database information and content of the content of the database, the update and maintenance of the database. As a result, the data provided by data analysts will also become an important basis for customized products and personalized services: with the help of advanced database technology, in -depth mining and multiple use of content resources, provide personal preference content services, or use digital printing with digital printing And publishing technology, realize the production of products on demand and delivery and printing.
In the requirements of data analysts of this paragraph
skill requirements
1. Undergraduate or above, mathematical statistics or data mining professional direction 2. Familiar with data analysis and data mining theory 3. Proficient in various use of various use Mathematical statistics, data analysis, data mining tool software 4. Those with e -mail work experience is preferred 5. Familiar with Internet application technology knowledge and network knowledge, understand the Internet and mail
other requirements
good communication ability , Text language expression ability, good logical analysis ability; have independent product planning and development capabilities, project management, business communication ability; strong responsibility, open personality, good communication skills; good at cooperation, good team cooperation Spirit; be able to carry out work under pressure; good at learning