Which is reliable for Beijing Big Data Analysis Training Class

Release time: 2024-05-15 10:44:05 Source: Youkao.com Comprehensive

Under the background of the digital economy and the trend of the artificial intelligence era, data analysts are professional international qualification certification oriented to the whole industry, aiming to improve the digital skills of the whole people, help enterprises to achieve digital transformation, and promote the digital development of the industry, CDA data analysts specifically refer to new data analysis talents who are specialized in data collection, cleaning, processing and analysis in the Internet, finance, retail, consulting, telecommunications, medical care, tourism and other industries, and can produce business reports and provide decision-making.

About Big Data

What exactly is big data?

Big data refers to a collection of data that cannot be captured, managed and processed with conventional software tools within a certain period of time. It is a massive, high growth rate and diversified information asset that requires a new processing model to have stronger decision-making power, insight and discovery power, and process optimization capabilities. The strategic significance of big data technology does not lie in mastering huge data information, but in specialized processing of these meaningful data. In other words, if big data is compared to an industry, the key to the profitability of this industry is to improve the "processing ability" of data and realize the "value-added" of data through "processing". "

Who is suitable for the data analysis course?

Want to go into business

Age 20-30 years old, college degree or above, no limitation on major/experience/gender.

have interest in

Be interested in data analysis, have certain anti pressure, patience and learning ability.

Want to change careers

People from all walks of life who want to change careers in IT, Internet, finance and other high paying industries.

graduate

The majority of fresh graduates and former graduates who intend to engage in data analysis related work.

Career development direction

Data analyst

Engaged in data collection, sorting, analysis, finding problems, analyzing problems, drawing conclusions, providing data support for the company's decision-making level, and focusing on business.

Data Mining/Algorithm Engineer

Using model training data to mine laws from massive data, predict or classify objects, mainly focusing on programming and algorithms, and requiring high statistical theoretical knowledge.

Data Product Manager

Mainly responsible for data oriented refining of demand, design, planning, project scheduling to project implementation, and later product improvement and optimization.

Data development engineer

Design, build, and maintain infrastructure to provide platforms for data collection, storage, processing, and computing. Partial code development needs to be compensated in terms of code capability, but compared with programmers in pure technology stacks, it needs some business logic.

Campus environment

Organization Introduction

Bo Wei Feng

Since its establishment, Boweifeng has been committed to providing IT vocational training for new graduates and new workers, and providing overall software testing solutions for customers at home and abroad. For many years, Boweifeng has always adhered to the teaching quality and sincerely served the students. Boweifeng has successively delivered software technology elites to many domestic and foreign enterprises. In the future, it will set up more training projects for talents in need according to industrial changes and technological innovation: help more recent graduates and new workers find satisfactory jobs and realize their career dreams; Help more employers easily recruit available talents, and promote enterprise development and industrial progress.

Beijing big data Which analysis training class is reliable? Boweifeng IT Vocational skills The training school, which is professional and reliable, has a good reputation and is an ideal place for you to learn IT skills. There are high-quality teachers and a variety of teaching methods, including offline teaching and online courses.

What are the employment prospects of data analysts?

1. Industry demand growth

In the next few years, the demand for data analysts is expected to grow significantly. Many enterprises are transforming to digital, and the demand for data is growing. They need professional data analysts to help them understand the data and obtain valuable business insights. In addition, with the continuous development of data science and machine learning technology, the role of data analysts will become more important.

2. Cross industry employment opportunities

Employment opportunities for data analysts are not limited to specific industries. In fact, almost all industries need data analysts. Whether in finance, medical care, e-commerce, manufacturing, or education, government, non-profit organizations and other fields, data analysts are needed to help them make data-driven decisions.

3. Change in skill requirements

The skill requirements of data analysts are also changing in the future. In addition to traditional statistical analysis skills and data visualization skills, data analysts also need to be familiar with big data technologies, such as Hadoop, Spark and data warehouse. In addition, they also need to master advanced technologies such as data mining and machine learning, as well as artificial intelligence and deep learning.

4. Salary level

The salary level of data analysts is usually high, which further proves the attractiveness of data analyst positions. The specific salary level will vary depending on the region, industry, work experience and other factors. However, generally speaking, the salary of data analysts is higher than other positions, especially in high-income industries such as technology and finance.

5. Career development path

The position of data analyst has many career paths. They can be gradually promoted from junior analysts to analysts, and eventually become data scientists or data engineering. In addition, they can also hold management positions within the enterprise, such as data department manager or chief data officer.

What to learn in data analysis

1. Data acquisition and cleaning: learn how to acquire data from various data sources, including databases, files, APIs, etc., and conduct data cleaning and pre-processing to ensure the accuracy and consistency of data.

2. Basis of statistics: understand basic statistical concepts and methods, such as probability, hypothesis testing, regression analysis, etc. This knowledge can help you understand data distribution, correlation and change trend.

3. Data visualization: learn how to use data visualization tools and technologies to transform data into charts, graphs and dashboards that are easy to understand and interact. This can better present the patterns, trends, and correlations of the data.

4. Data analysis technologies and tools: familiar with common data analysis technologies and tools, such as SQL, Python, R, etc. These tools provide rich functions and libraries for data processing, statistical analysis, machine learning, etc.

5. Data mining and machine learning: understand the basic concepts and methods of data mining and machine learning. These technologies can help you find hidden patterns and trends in data, and build prediction models and classification models.

6. Data interpretation and story telling: learn how to interpret and convey the results of data analysis. Master effective communication and story telling skills, and be able to transform complex data analysis results into understandable language and charts, and convey insights to non-technical personnel.

7. Domain knowledge: understand the characteristics and business needs of your field. Deeply understanding the industry background and business processes can better analyze and interpret the data.

More training courses: Beijing Boweifeng Big Data Analysis Training Course More school information: Beijing Boweifeng IT Vocational Training Consulting telephone: