More and more institutions view data. From the Ministry of National Defense to Internet startups and financial institutions, big data projects are needed, and there is a lot of work that needs data analysis or processing. Common food manufacturing, retail e-commerce, medical manufacturing and traffic detection also need data analysis and processing, such as optimizing inventory, reducing costs and forecasting demand. Talents are mainly divided into three categories: big data system research and development, big data application development, and big data analysis. Popular positions are:
1. big data system architect
Big data platform construction, system design and infrastructure. Skills: computer architecture, network architecture, programming paradigm, file system, distributed parallel processing, etc.
2. Big data system analyst
Facing the actual industry field, we use big data technology to manage, analyze and apply the data security life cycle. Skills: artificial intelligence, machine learning, mathematical statistics, matrix calculation, optimization method.
3.hadoop development engineer.
Solve the problem of big data storage.
4. Data analyst
Professionals in different industries who specialize in collecting, sorting out and analyzing industry data and conducting 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, you need to be proficient in at least one data analysis software such as SPSS, STATISTIC, Eviews, SAS, big data magic mirror, at least use Acess to develop databases, at least master one mathematical software such as matalab and mathmatics to build new models, and at least master one programming language. In short, an excellent data analyst should keep up with his business, management, analysis, tools and design.
5. 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++. Sometimes write programs with MapReduce, and then process data with Hadoop or Hyp. If you use Python, combine it with Spark.
6. 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 heroes.
Responsibilities of big data visualization engineer: 1. According to the business function of the product, design a visual scheme that meets the requirements. 2. According to different visualization scenarios and performance requirements, choose the appropriate visualization technology. 3. Make visual samples according to the scheme and technical selection. 4. Cooperate with visual designers to improve visual paradigms. 5. Cooperate with front-end developers to componentize the samples.
Want to know more about the work of big data, "CDA data analyst" refers to a new type of data analyst who specializes in data collection, cleaning, processing and analysis in Internet, finance, retail, consulting, telecommunications, medical care, tourism and other industries, and can make business reports and provide decisions.