1, high number big data technology.

Big data technology is an interdisciplinary subject involving mathematics, computer science, statistics and other fields, in which mathematics is an important foundation. When learning big data technology, you need to master the knowledge of calculus, linear algebra and probability theory in advanced mathematics, which is the foundation of big data technology.

2. The main technologies of big data.

Big data technology needs to be able to efficiently collect and store a large amount of data. In terms of collection, data can be collected through sensors, log files, social media and other channels; In storage, distributed file system, database, data warehouse and other technologies are used to store data.

3. Understand the advantages of big data technology.

Big data technology is one of the high-paying occupations. With the continuous expansion of the application scope of big data, talents who master relevant technologies are scarce, so the wage level in the field of big data is relatively high. By learning and mastering big data technology, you can have the opportunity to get higher salary.

High-number employment direction of big data technology;

1, data analyst.

As a data analyst, you will use mathematical statistics to solve practical problems, and at the same time use big data technology to process and analyze massive data. You can extract valuable information and patterns from data according to business requirements and present the results to decision makers.

2. Data scientist.

As a data scientist, you will deeply study and analyze data, build models and algorithms to solve complex data problems. You need to combine the mathematical modeling ability of high numbers with big data technology to carry out data preprocessing, feature engineering, machine learning modeling and so on.

3. Data engineer.

As a data engineer, you will be responsible for building and maintaining the infrastructure for big data processing and analysis. You need high mathematical modeling ability to design and optimize data processing flow, data storage scheme and big data computing platform. In addition, you need to be familiar with data cleaning, data integration, ETL and other technologies to ensure the quality and reliability of data.