SAS: Large data age data scientists will become scarce talent

Industry analyst Software and service provider SAS said in a recent company publication that the demand for data scientists in the big data age would soar, and that a shortage of talent would be a new challenge for companies.

SAS points out that the advent of the big data age shows the amazing value of large data analysis for business development, at the same time, large data volume, unstructured, data sources are complex, making large data processing and analysis need to be different from traditional data analysis of new technologies (such as high-performance analysis hpa) and new talent.

Data scientists positioning

Data scientists set the role of technical experts and quantitative analysts. The difference between them and the traditional quantitative analyst is that the latter usually use the internal data of the enterprise to analyze to support the leadership decision-making, while the former is more to create different characteristics of products and processes by focusing on the user-oriented data, and to provide customers with meaningful value-added services. Customer-oriented nature determines that most data scientists work in the company's product development or marketing department, or in the chief technology officer.

Data scientists focused on high-performance analysis are not necessarily experts in unstructured data processing, but they need to explore different ways to use high-performance analysis (HPA)-saved time to continually refine the analysis model and improve the decision speed to match the faster lifecycle of data analysis.

Data scientists essential skills

Data scientists need to have comprehensive skills in technology, business, analysis, and relational science. Many data scientists have a degree in Advanced computer Science, or a series of advanced degrees in physics, bioscience or social science that require a considerable amount of computer skills. Data scientists are facing and processing up to terabytes of data, which requires them to master a considerable amount of expertise, and SAS concludes the following six points:

• Ability to handle distributed file system tools such as Hadoop, MapReduce, etc.

python, Java, pig and hive programming languages

• Machine learning Ability

• Non-traditional database tools such as Vertica and MongoDB

• Natural language Processing

• Use of statistical tools

In fact, with these advanced degrees and professional skills is not enough, data scientists also need to have an analyst quality, such as math and statistical skills, a keen sense of business acumen, and the ability to communicate effectively with customers, product managers and decision makers. Of course, to have an employee with all of the above capabilities is not easy to do, so many enterprises set up a specialized data science team, hope that through the combination of talent, comprehensive response to a variety of needs.

Recruiting and nurturing data scientists

"Big data will be the new standard in the next 10 years, and a decade of research on Orlando systems and data will be a very common phenomenon," Gartner, an independent research institute, said at the Symposium/itxpo conference in 2012 in Florida. But at present, the industry is very short of all the data and the use of data is very familiar with the data scientists, our public and private education system does not meet our needs in this area. Data experts will be a rare and valuable asset. ”

There are few professional courses on data science currently in institutions of higher learning, but some institutions have begun to try to work with companies like SAS to open up one or several targeted professional courses and open them up to the outside. Some companies interested in developing large data services or services have started to set up in-house training courses to nurture future data scientists from within the enterprise, such as EMC, which offers "data Science and Data analysis" courses for in-house employees and customers. Some consulting firms are also starting to provide their clients with the data they need to be scientists.

SAS encourages companies to start data as soon as possible in the context of a big data age. The talent reserve of scientists will help to enhance the core competitiveness of enterprises.

SAS has nearly 40 years of experience in advanced Business Analytics and has been looking for ways to sow the seeds of new technology and advanced knowledge since SAS was founded in the United States North Carolina State. In the United States, SAS software designed for educators and students is used by more than 35,000 teachers in 6,000 schools, and the university uses SAS software for more than 36 years.

In China, SAS held last year to "build the power of knowledge, seize the future opportunities," the National University tour is very successful, this year will continue through technical lectures, on-site exchanges and other means, to the teachers and students in today's large data trends intelligent analysis solutions and other technical developments, through the sharing of typical applications, Let more students in school master Business Intelligence technology to help them improve their competitiveness in the future job market.

(Responsible editor: Fumingli)