Big data learning doesn't need math. Good. Big data is mainly about learning, testing and exercising logical thinking of programming technology. If you study data analysis, you need to have a foundation in mathematics and statistics, and the requirements are not very high. You can learn it well as easy as blowing off dust.

1. Big data analysis needs the foundation of mathematics and statistics.

2. Big data development mainly focuses on learning programming technology and does not require mathematical foundation.

Both big data development course and data analysis course are suitable for zero-based learning. When learning, you need to choose a learning method that suits you. Zero-based learning is generally to find someone to take or find a training class.

Big data can be widely used in medical industry, energy industry, communication industry, retail industry, financial industry, sports industry and other industries, providing technical support for data collection, transmission, storage and analysis, which is not only convenient and fast, but also brings huge economic value to the industry. Companies that provide big data infrastructure and big data software technical services are also developing rapidly.

1, big data development engineer

Big data engineering needs to solve the work of data definition, collection, calculation and storage, so when designing and deploying such a system, big data engineers should first consider the high availability of data.

2. Data analysis

How to use data, that is, how to provide productive data analysis for enterprises or organizations after receiving data from big data engineering system, and can really help companies improve their business or improve their service level.

3. algorithm engineer

From the research field, there are mainly audio/video algorithm processing, two-dimensional information algorithm processing in image technology and one-dimensional information algorithm processing in communication physical layer, radar signal processing, biomedical signal processing and other fields. In addition, data mining and Internet search algorithms, which reflect the development direction of big data, have become more and more popular in recent years, and algorithm engineer has gradually developed towards artificial intelligence.

4. Data Mining Engineer

It can also be called "data mining expert". Data mining is a technology to discover its laws from a large number of data by analyzing every data. Data mining is a decision support process, which is mainly based on artificial intelligence, machine learning, pattern recognition, statistics, database, visualization technology and so on.