Data Science in the Business Environment: Skills Analytics for Curriculum Development

• Published in: Machine Learning, Optimization, and Data Science Vol. 11331; pp. 116 - 128
• Main Author: Lu, Jing
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2019; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Analytical tools; Business analytics; Business intelligence; Data mining; Machine learning; SFIA; Skills frameworks; Subject benchmarks
• ISBN: 3030137082; 9783030137083
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-13709-0_10

Data science is an interdisciplinary field of methods, processes, algorithms and systems to extract knowledge or insights from data. University of Winchester Business School, UK is developing an undergraduate degree programme in Data Science which brings together student-centred and business-driven approaches: positioning the course for the interests of students and requirements of employers. The new programme follows the expectations of relevant subject benchmark statements and is built on activities which focus on different aspects of data science, drawing on some existing modules as a base. It integrates key themes in information management, data mining, machine learning and business intelligence. This paper presents the ongoing development of the Data Science programme through the key aspects in its conception and design. Understanding the employment market while defining specific skills sets associated with potential graduates is always important for courses in higher education. The Skills Framework for the Information Age (SFIA) has been adopted and a novel mapping proposed for the interpretation of employability skills related to data science. These are then linked to an adapted process model as well as the specialist modules across academic levels.