What are the requirements for a big data visualization engineer

The essence of data visualization is visual conversation. Data visualization combines technology and art to convey and communicate information clearly and effectively with the help of graphical means.

The meaning of visualization is to help people better analyze data, and the quality of information depends largely on the way it is expressed. Analyze the meaning of the data composed by the numerical list and visualize the results of the analysis.

The main role of data visualization is to visually convey key data and features through graphics and colors, so as to achieve a fairly sparse and complex data set.

Insights. And simply say"Data presentation"Not exactly, because data visualization does not cover all data without differences, and the process of visualization itself has already added the producer's thinking, understanding, and even some assumptions about the problem, while data visualization helps the producer obtain guidance or verification at the objective data level in a clear way.

The job requirements for a big data visualization engineer are as follows:

First, it needs to be statistics, applied mathematics, and computer science.

Bachelor's degree or above.

Second, you need to have internship experience or experience in big data competitions.

Third, be proficient in at least one big data tool, Python R, or other data mining.

and data presentation software.

Fourth, it is necessary to have a good ability to write data analysis reports, and have a certain ability to visualize, scientific and aesthetic graphics effects.

What are the requirements for big data visualization engineers, Qingteng will share with you here. If you have a strong interest in big data engineering, I hope this article can be helpful to you. If you also want to know more about data analysts, big data engineers.

You can click on other articles on this site to learn.

Big data engineers are mainly analyzing the history, the future, and optimizing choices, which are the three most important tasks of big data engineers when "playing with data".

Identifying the characteristics of past events: An important job for a big data engineer is to analyze data to find characteristics of past events. Identifying the characteristics of past events can be most useful in helping businesses better understand consumers.

By analyzing the user's past behavior trajectory, we can understand the person and his behavior.

What the future may happen: By introducing the key factors into the field, big data engineers can be able to import future consumer trends.

Find out the optimal results: Depending on the nature of the business of different enterprises, big data engineers can imitate data analysis to achieve different purposes.

Summary. If you want to be a big data visualization engineer, is it competitive to be a bachelor's degree graduate?

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It's not hard to become a data visualization engineer, just take your data visualization course. The key depends on what the future career development direction is, whether to start a business or be a professional worker.

Therefore, data visualization engineers have two directions, one is to master data visualization tools or technologies and provide data visualization services for others or enterprises; Another category is the development of data visualization products.

In addition to learning the use of data visualization software, the first type of engineer also needs to understand some business or management knowledge. The second category requires a strong computer background and a variety of programming skills.

1.Data Analyst.

A data analyst can gain insight into the business implications of an equation. They know how to ask the right questions and are very good at data analysis, data visualization and data presentation. Whether giving a presentation to another data analyst or a C-level executive, a data analyst is an expert at data extraction, pattern recognition, and insight into problems from large amounts of data.

2.Data Visualization().

The quality of the information depends heavily on the way it is expressed. One of the most important skills for a data scientist is to analyze the meaning contained in the data composed of numbers, develop web prototypes, and use external APIs to unify other services such as charts, maps, dashboards, etc., to visualize the results of the analysis.

Both of these have their pros and cons, depending on which aspect you fancy is trembling, overall, this is the general direction of the future.

Data visualization is a scientific and technological research on the visual representation of data, and it is necessary to do big data development.

The visual representation of such data is defined as a kind of information extracted in some summary form, including the various attributes and variables of the corresponding information unit. Wangzhou Technology has its own unique insights and experiences in data analysis and visualization, focusing on the practical application analysis of Adobe data products in the United States.

It is a concept that is constantly evolving, and its boundaries are constantly expanding. Refers primarily to technically advanced technical methods that allow the use of graphics, image processing, computer vision, and user interfaces.

Visualize and interpret data through representation, modeling, and display of stereoscopic, surface, attributes, and animations. Compared to special technical approaches such as stereo modeling, data visualization covers a much broader range of technical approaches.

The research direction of big data technology and application is the "Internet +" cutting-edge technology major that combines cutting-edge technologies such as big data analysis, mining and processing, mobile development and architecture, software development, and cloud computing. This major aims to train students to systematically master data management and data mining methods, and become senior professional big data technical talents with the ability of big data analysis and processing, data warehouse management, comprehensive deployment of big data platform, big data platform application software development and visual display and analysis of data products.

Specifically, you can do this:

Retail: Mainly focusing on customer marketing analysis, through big data technology can analyze customer consumption information. Obtain the customer's consumption habits and consumption direction, so that the shopping mall can do a better job of more reasonable commodity and shelf placement, plan marketing plans, product recommendation methods, etc.

Financial industry: In the financial industry, data is life, and a large number of customer transaction data has been accumulated in its information system. Through big data, customer behavior can be analyzed, fraud prevention and financial risk analysis can be analyzed.

Healthcare: Big data can assist in analyzing epidemic information and make corresponding prevention and control measures. Trend analysis of human health can improve diagnostic accuracy and drug effectiveness in electronic medical records, medical research and development, and clinical trials.

Manufacturing: The industry's demand for big data is mainly reflected in product development and design, chain management, production, after-sales service, etc. Through data analysis, unnecessary steps can be eliminated in the product development process and the manufacturing and assembly process of products can be improved in a timely manner.

If you want to know more about what big data technology and application is, what it does, and what are the employment prospects, you can go to the CDA Data Analysis Certification Center to learn more. CDA is the abbreviation of data analysis professionals in the era of big data and artificial intelligence, which refers to new data talents who specialize in data collection, cleaning, processing, analysis and can make business reports and provide decision-making in industries such as Internet, finance, consulting, telecommunications, retail, medical care, and tourism.

Visualization technology is a theory, method and technology that uses computer graphics and image processing technology to convert data into graphics or image form and display it on the screen, and carry out interactive processing. You don't need to know this to do big data development, what you need to know is the development technology of components in the Hadoop ecosystem, such as SPATK, HBase, etc., you can refer to the syllabus of Badou Academy to learn.

Big data visualization has always been one of the core contents of big data research, and the ability of computer automatic analysis is used to assist people to analyze and mine the information behind big data more intuitively and efficiently.

A big data visualization engineer needs to be responsible for pushing big data visualization related products; Suggestions and solutions related to constructive visualization products and interactions; Responsible for the application of graphical tools and means in the collected high-quality data to reveal the complex information in the data at a glance; According to the product strategy and presentation logic analysis and calculation, the presentation data is extracted and integrated, etc.

Big data development doesn't necessarily require big data visualization technology, but big data analysts do.