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Dr Richard S Wilson FHEA, MBCS

Course Leader, MSc Big Data Analytics


Richard Wilson is the course leader for the MSc in Big Data Analytics within the College of Business, Technology and Engineering, department of computing, and the Maths department at Sheffield Hallam University. He teaches on both undergraduate and postgraduate modules and is an advanced user of the SAS® software suite, which he uses for both teaching and research. His main teaching focuses on SAS Programming, Data Warehousing and Data Mining, Data Integration, Applied Business Intelligence, Text Mining and Research Principles and Practices.


After achieving a distinction in his Master's degree in Business Intelligence, Dr Wilson started his professional career as researcher, in the Operations Research department at Warwick Business School. He then went on to work as a Business Analyst in the NHS where he was quickly promoted to Senior Information Analyst. Dr Wilson gradually progressed into research using SAS software, as part of a multimillion pound EU funded research project and for his own PhD research. He is now MSc Course Leader in Big Data Analytics at Sheffield Hallam University. His main teaching focuses on SAS Programming, Data Warehousing and Data Mining, Data Integration, Applied Business Intelligence, Text Mining and Research Principles and Practices. He has also written a number of papers on the use of Data Mining and is actively engaged in research in this field.

Business Intelligence
Data Warehousing
Data Mining
Higher Education


Department of Computing

Information Systems

MSc Big Data Analytics


Data Warehousing and Data Mining
Software Tools and Databases

Maths Technology
Applied Business Intelligence


Data Integration
Advanced Statistical Modelling and Data Mining

Applied Business Intelligence
Advanced Data Management
Data Mining
Data Warehousing
Research Skills
R Studio
SAS Programming


Journal articles

Yates, S., Akhgar, B., Bates, C., Jopek, L., & Wilson, R. (2011). A platform for discovering and sharing confidential ballistic crime data. International Journal of Knowledge and Web Intelligence, 2 (2/3), 202-218.

Conference papers

Wilson, R.S.I., Ginige, A., Goonetillake, J.S., & Indika, W.A. (2019). User needs-driven enrichment of ontology: A case study in Sri Lankan Agriculture. ACM International Conference Proceeding Series, 581-586.

Wilson, R., & Burley, K. (2012). Understanding student progression for data mining analysis. Fifth Annual Conference of the Higher Education Institutional Research Nework for the United Kindom and Ireland.

Wilson, R., Jopek, L., & Bates, C. (2010). Sharing ballistics data across the European Union. In IARIA, Lisbon, Portugual, 10 November 2010. IARIA

Jopek, L., Wilson, R., & Bates, C. (2010). An application of a domain-specific language facilitating abstraction and secure access to a crime and ballistic data sharing platform. In IARIA, Lisbon, Portugual, 10 November 2010 (pp. 29-33). IARIA

Yates, S., Jopek, L., Mitchell, S., & Wilson, R. (2009). Semantic interoperability between ballistic systems through the application of ontology. In IADIS (International Association for Development of the Information Society) International Conference in Applied Computing 2009, Rome, Italy, 19 November 2009 - 21 November 2009.

Yates, S., Jopek, L., Mitchell, S., Wilson, R., Calderelli, L., & Fortune, D. (2008). The Odyssey platform: a unified European response to a global threat. In Conference.

Book chapters

Mcseveny, K., & Waddington, D. (2011). Up close and personal : the interplay between information technology and human agency in the policing of the 2011 Sheffield Anti-Lib Dem protes. In Akhgar, B., & Yates, S. (Eds.) Intelligence management : knowledge driven frameworks for combating terrorism and organized crime. (pp. 199-212). Springer:

Yates, S.J., Bates, C., Akhgar, B., Jopek, L., Wilson, R., Mitchell, S.J., & Killick, S. (2011). The odyssey project – understanding and implementing user needs in the context of ballistic crime data exchange. In Advanced Information and Knowledge Processing. (pp. 11-34).

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