What is an Internet data analyst and what exactly does a network data analyst do?

Do you mean Internet data analysts in the direction of the Internet industry? I think you need to have a certain foundation to become a data analyst.

In general, data analysts don't have that much data or statistical knowledge because you're not doing data mining. Data analysis, on the other hand, mostly calculates some numerical features of existing data, analyzes some data trends, gives some descriptive analysis in combination with some actual backgrounds, and uses some common statistical models at most to further analyze the data. However, due to the popularity of data mining or big data nowadays, simple statistical models are also operated by data miners in the case of models.

Therefore, from the perspective of statistical expertise, it is enough to know the most basic knowledge of probability theory and mathematical statistics, as well as the knowledge of some common models including regression analysis, time series analysis, multivariate statistical analysis, etc.

It is best to learn data analysis with some basic data analysis software operations, such as the most commonly used SAS and SPSS, for some foreign companies or pharmaceutical companies, most of them prefer SAS, because SAS is a more authoritative statistical software. For some social science and economic companies, there are more corresponding SPSS because it is simple and easy to operate, but because of this, the demand for statistical talents is not so great.

In recent years, there have been many requests for database knowledge and related software. The more demanding ones here are SQL, MySQL, SQL Server, etc. It is also because of the massive amount of data that more professional software is needed for data storage, extraction, and maintenance, which came into being.

Moreover, many companies also use these software to maintain and clarify the data, and then they can analyze the data.

Different from general data analysts, they focus more on analyzing the data of the vertical Internet industry, and are more concerned about taking Internet data as the center to guide consumer behavior and promote Internet business decisions. The data analysis course of the big podium is mainly biased towards this area.

Data analysts mainly work in the following aspects:

First, for product managers, domestic product managers do not understand data analysis, and the competitive intelligence analysis of new products, product agile testing, etc. need to be completed with the help of data analysts, and later product iteration optimization still needs data analysts to collect user behavior, habits, evaluation and other data to complete;

The second is to serve the operation, and the user flow, customer relationship management, etc. in the product operation need to be completed with the help of data analysts; Third, the company's data formulation and standard construction, data integration of various departments, data management and other work need to be completed by data analysts;

Fourth, data intelligence and data ** serve the high-level.

From the above four aspects, business analysis ability and business knowledge ability are particularly important, this time is to test the analyst's business understanding ability and ability to solve practical problems for enterprises through data. For example, the analyst's analytical process, analytical thinking, analytical skills, and demonstrated persuasion. You can consider entering a professional company in this area, or if you are lucky enough to meet an experienced teacher to take you for a while, like I was lucky enough to meet a teacher to take me when I entered Cassia Ming, and I made rapid progress, so now I am basically very proficient in this set.

What is data analytics for?

Collecting, calculating, and making data available to other departments in the enterprise.

What is data analysis used for?

From a workflow perspective, there are at least 5 types of analysis that are often done:

Planning analysis before the start of work: to analyze what is worth doing before the start of the work**type analysis: ** the current trend, the expected effect of the monitoring analysis in the work:

Monitor the trend of indicators and find the cause of the problem: analyze the cause of the problem and find the countermeasure after the review analysis: accumulate experience and summarize lessons.

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So what is data analysis?

Data analysis is broadly divided into 3 steps:

1: Get data. Obtain user behavior data through burying points, and open up internal system data through data synchronization. and the construction of data warehouses to store data.

2: Calculate data. According to the analysis requirements, extract the required data, calculate the data, and make tables.

3: Interpret the data. Interpret the meaning of the data and derive some useful conclusions for the business.

So do data analysts mainly do the above three things?

It's not all, this is different in different companies. If the company is large, the acquisition of data is often done by the data development team, and their position is usually "data development engineer" or "big data engineer". Interpreting data is to write your own PPT for interpretation, leaving it to the "data analyst", which is actually a step in the middle of calculating data.

Some companies (generally doing e-commerce), the data is directly exported from platforms such as **, Tmall, Amazon, etc., and then analyzed based on these data. In some companies (generally traditional enterprises), the data is directly used in large-scale BI products, and then everyone exports data analysis based on BI products, and some companies are very small, so they directly do everything from data burying to data warehouse to data withdrawal.

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Data analysts generally refer to the business direction, discover business problems through data, gain insight into industry opportunities, and drive the development of enterprises through the value generated by data, which is also the most needed talent for the digital transformation of enterprises. It requires less programming ability, and if you have accumulated previous work experience in other areas, it will be helpful to develop in this direction, and the learning pressure will be reduced accordingly.

What profession is suitable for data analyst? In fact, in 2016, there were universities in China to set up big data-related majors, and the first batch of graduates graduated in 2020. So now data analysts are in short supply, and all walks of life need data analysts, don't worry too much about being affected by the profession.

Now the school or the teacher, in fact, there is no data analysis front-line work experience, the company's actual demand for data analysis schools and teachers are actually not real docking, our country's college education is about 10 years later than the market, last year's graduates, most of the professional outdated theoretical knowledge, no practical experience, completely unable to meet the needs of the enterprise, so, up to now, the market is equivalent to no professional professional data analysts.

If you really want to learn data analysis, Jiudaomen data analysis suggests that you should focus on project experience and get in touch with real data projects.

A data analyst is a data scientist datician[.]'DETN] refers to professionals in different industries who specialize in collecting, collating, and analyzing industry data, and making industry research, evaluation, and research based on data.

Data Analyst Skill Requirements:

1. Understand business. The premise of engaging in data analysis will be to understand the business, that is, to be familiar with industry knowledge, the company's business and processes, and it is best to have your own unique insights.

2. Understand management. On the one hand, it is the requirement to build a data analysis framework, for example, to determine the analysis idea, it is necessary to use marketing, management and other theoretical knowledge to guide, if you are not familiar with management theory, it is difficult to build a data analysis framework, and it is difficult to carry out follow-up data analysis. On the other hand, it is used to provide instructive analysis suggestions for the data analysis conclusions.

3. Understand analysis. It refers to mastering the basic principles of data analysis and some effective data analysis methods, and being able to flexibly apply them to practical work in order to effectively carry out data analysis. The basic methods of analysis are:

Comparative analysis, group analysis, cross-analysis, structural analysis, funnel analysis, comprehensive evaluation analysis, factor analysis, matrix correlation analysis, etc. Advanced analysis methods include: correlation analysis, regression analysis, cluster analysis, discriminant analysis, principal component analysis, factor analysis, correspondence analysis, time series, etc.

4. Understand tools. Refers to mastering the common tools related to data analysis. Data analysis method is theory, and data analysis tools are tools to realize the theory of data analysis methods, in the face of more and more huge data, we can not rely on calculators for analysis, we must rely on powerful data analysis tools to help us complete data analysis work.

5. Understand design. Understanding design refers to the use of charts to effectively express the analytical views of data analysts, so that the analysis results are clear at a glance. The design of charts is a major matter, such as the selection of graphics, the design of layouts, the matching of colors, etc., all of which need to master certain design principles.

For more information about data analysts, we recommend going to the CDA Data Certification Center to learn more. 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.

What is a Data Analyst Certificate?

Data is the user's behavior trajectory in the company's products. Therefore, the ultimate solution for network data analysts is to make user behavior transparent, help the company's decision-making department and operation department make better judgments and operational decisions, and promote business growth.

Transparency of user behavior. According to the technical environment used by the company, you need to understand SQL and database pulling. You may also need to understand business, user psychology, and reporting tools (such as Tableau, PowerBI, Excel, etc.), such as showing the user's behavior trajectory from browsing to placing an order in the funnel.

Help the company's decision-making department and operation department make better judgments and operational decisions. Due to the differences in the ability and means of intervention of different companies' operating departments and product departments to users, there are many differences. Therefore, you need to understand the resources mastered by the operation department you dock, understand the product's ability to intervene in users, understand competitors, and use analysis reports (i.e., the so-called data method of the best ones) to tell the relevant decision-makers that the current problems are in the first place, where there is potential, and what means we can use to do business growth and promote business forward, so as to realize our own value, and at the same time our own salary and job promotion.

A data analyst is a data scientist datician[.]'DETN] refers to professionals in different industries who specialize in collecting, collating, and analyzing industry data, and making industry research, evaluation, and research based on data.

At present, there is a large talent gap, and it is relatively easy to get started. Data analysis does not require a strong science and engineering background, but those with a background in marketing, finance, finance or retail will have a more open analytical mind.

The salary package is high. The average monthly salary for a big data analytics position with 1 or 2 years of work experience can reach the level of about 13k. The salary of the position is positively correlated with experience, and the older you are, the more valuable it is.

What does a data analyst do? A data analyst is one type of data engineer, and the other is a data mining engineer, both of which are professionals.

The main tool used by a data analyst can be programming, but it is not necessary;

Because there are a large number of powerful and easy-to-use data analysis tools, such as Excel, Tableau, SPSS, SAS, etc., even if you don't have programming skills, you can still be competent for most data analysis work;

At the same time, since Internet companies are now talking about big data, and the storage of data is basically in various big data platforms and databases, it is necessary for you to master the use of HIVE, HDFS, MYSQL, etc., and it is inevitable that you will be proficient in SQL.

There are generally two types of data analysts: one is business-oriented, which mainly provides support for the needs of various business lines, product managers, operations, and department leaders, helping them analyze the business, understand the business, discover the problems in the business and provide solutions; The other is a macro analysis, generally there is no demand side, mainly spontaneous exploration, take the initiative to find the problems existing in the company's business, figure out the company's development trend, and guide the direction of the company's development.