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2019 | OriginalPaper | Chapter

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

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Abstract

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.

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Literature
1.
go back to reference Abbott, D.: Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst. Wiley, Indianapolis (2014) Abbott, D.: Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst. Wiley, Indianapolis (2014)
4.
go back to reference Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. 11(1), 10–18 (2009)CrossRef Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. 11(1), 10–18 (2009)CrossRef
6.
go back to reference Marr, B.: Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results. Wiley, Oxford (2016)CrossRef Marr, B.: Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results. Wiley, Oxford (2016)CrossRef
7.
go back to reference Marr, B.: Key Business Analytics: The 60 + Business Analysis Tools Every Manager Needs to Know. Pearson, Harlow (2016) Marr, B.: Key Business Analytics: The 60 + Business Analysis Tools Every Manager Needs to Know. Pearson, Harlow (2016)
8.
go back to reference Provost, F., Fawcett, T.: Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. O’Reilly Media, California (2013) Provost, F., Fawcett, T.: Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. O’Reilly Media, California (2013)
15.
go back to reference Shearer, C.: The CRISP-DM model: the new blueprint for data mining. J. Data Warehouse. 5(4), 13–22 (2000) Shearer, C.: The CRISP-DM model: the new blueprint for data mining. J. Data Warehouse. 5(4), 13–22 (2000)
Metadata
Title
Data Science in the Business Environment: Skills Analytics for Curriculum Development
Author
Jing Lu
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-13709-0_10

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