The University of Hong Kong
Competence in essential analytics skills gives Graduates competitive edge for tomorrow’s data-driven business world
Statistics have become more important than ever in the era of big data. Data, and the value of analytics continues to increase in the business sector and in the wider community. There is also growing demand for talent equipped with the essential skills in analytics. In view of this burgeoning need for analytics talent, the master of statistics degree program at the University of Hong Kong incorporated data mining into the curriculum in 2003, becoming the first to do so in the local academic world.
Sound knowledge of SAS’s software will give our students competitive advantage after graduation, be it for job application or career advancement.
Professor WK Li
Department of Statistics and Actuarial Science, University of Hong Kong
Prof. WK Li (Right), Head of Department of Statistics & Actuarial Science and Dr. Philip Yu (Left), Associate Professor of Department of Statistics & Actuarial Science
Since the mid-1980s, the master of statistics program at the University of Hong Kong has been integrating applications and techniques from SAS into their teaching curricula.
Professor WK Li at the Department of Statistics and Actuarial Science, the University of Hong Kong, says, “Mastery of data analytic software including those developed by SAS is essential. As the world’s leading statistical software provider, SAS’s software is extensively adopted by leading organizations worldwide. SAS is the software used for data analysis and risk management in many banks, financial institutions and government departments. Competence in SAS software will give our students a competitive edge when looking for a career in a global business enterprise.”
Data mining is a core aspect of business analytics. To better equip students for careers in the business analytics industry, the program has incorporated SAS Enterprise Miner into their teaching. Fast, easy and self-sufficient, this user-friendly data-mining software makes the learning of data mining techniques much simpler, introducing methods and techniques such as sophisticated data preparation, summarization and exploration, predictive and descriptive modelling, reporting and management. The software allows students to develop effective descriptive and predictive modelling and gain insights that drive better decision making in a business context.
A number of major global corporates have built their entire business model around analytics. “Sound knowledge of SAS’s software will give our students competitive advantage after graduation, be it for job application or career advancement,” Professor Li says.
Professor Li is pleased with the program’s success in nurturing analytics talent for business. “2017 marks a significant milestone for us, as it will be the 50th anniversary for the Department of Statistics and Actuarial Science, as well as the 30th anniversary for the Master of Statistics. Over three decades, we have more than 800 graduates from this program, part-time and full-time students included. Our graduates go into a diverse portfolio of business sectors, including treasury, assessment management analysis, risk management and fraud risk analysis, among others.
Looking forward, with the continued growth of big data, and especially in the context of the Internet, IoT and social media, the department wants to take the lead in understanding how other faculties within the university leverage on Big Data and then serve in an advisory role for other departments, with the support of SAS’s solutions in teaching. “We believe that deploying SAS analytics tools is one of the most effective ways to build students’ professional skills and theoretical knowledge in this area, and prepare them to meet the challenges in tomorrow’s data-driven business world,” says Professor Li.
Give students real-world experience in the classroom so that they have a competitive advantage in the job market.
SAS® Enterprise Miner
Graduates enter the workforce with business intelligence and predictive analytics know-how that commands higher starting salaries.