Who are the graduates of big data jobs and what can they do?

Big data work mainly focuses on data value, involving data collection, data collation, data storage, data analysis, data security, data application and many other aspects.

Big data jobs From the perspective of big job division, the current big data jobs can be divided into development jobs, algorithm jobs (data analysis), and operation and maintenance jobs. The task of the development post involves two aspects, one is to complete the business realization, and the other is to complete the data production. At present, many traditional software development tasks are gradually transitioning to big data development, which also leads to a greater demand for talents in the current big data development positions. Engaged in big data development positions, we also need to focus on learning cloud computing related knowledge, especially PaaS.

The algorithm post is also closely related to the scene, but because the algorithm post requires higher practitioners, it often needs higher education to support it. Because of the high added value of posts, many graduate students, including doctoral students, are keen on posts, which leads to fierce competition for posts. In addition, there are some bottlenecks in the application of artificial intelligence technology, so the algorithm post has also cooled down.

The demand for talents in big data operation and maintenance positions is relatively large, and the coverage of big data operation and maintenance positions is also very wide. Data collection, management, storage, security, big data platform construction and other contents can be classified as big data operation and maintenance positions, and engaging in operation and maintenance positions also requires a lot of network knowledge and server knowledge.

Big data employment direction 1, big data development engineer

Big data development engineer, a popular technical talent that many companies are recruiting, has a higher salary than other directions. To be a big data development engineer, you need to master computer technology, hadoop, spark, storm development, hive database, Linux operating system and other technologies, such as distributed storage and distributed computing framework.

2. Big Data Analyst

Big data analyst is a kind of data analyst, which refers to professionals in different industries who specialize in the collection, collation and analysis of industry data, and make industry research, evaluation and prediction based on the data. In our work, we use tools to extract, analyze and present data to realize the commercial significance of data.

As a data analyst, I will use at least one of the data analysis software such as SPSS, STATISTIC, Eviews, SAS, and big data mirroring. Should be proficient in using at least one mathematical software such as matalab and mathmatics to develop databases, and master at least one programming language. In short, an excellent data analyst should keep up with his business, management, analysis, tools and design.

3. Data Mining Engineer

To discover laws from massive data, data mining needs certain mathematical knowledge, such as linear algebra, advanced algebra, convex optimization, probability theory and so on.

Commonly used languages are Python, Java, C or C++, and I use Python or Java more myself. Sometimes write programs with MapReduce, and then process data with Hadoop or Hyp. If you use Python, combine it with Spark.

4. Big Data Visualization Engineer

With the application of big data in people's work and daily life, big data visualization has also changed the way people read and understand information. From the migration of Baidu to the flu trend of Google, and then to the launch of county economic visualization products in Alibaba Cloud, big data technology and big data visualization are all behind the scenes.