Nifty with data: can a business intelligence analysis sourced from open data form a nifty assignment?

LOVE, Matthew, BOISVERT, Charles, URUCHURTU, Elizabeth and IBBOTSON, Ian (2016). Nifty with data: can a business intelligence analysis sourced from open data form a nifty assignment? In: ITiCSE '16 : Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education. ACM. (In Press)

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This paper proposes a *nifty assignment* in data mining and discusses how quality in database assignments differs from other domains in computer science, particularly programming. It then considers the sources of data used, to study whether Open Data can form the basis of more such assignments, and if so how. In the next sections, we describe the nifty assessment criteria and explain why use them as a standard for quality of assessment. We then propose an assignment which outlines a number of topics related to finding and accessing Open Data, merging sources, and analysing the data using self-service and data mining tools. Once the assignment is clear, we will reconsider it against the nifty criteria, but also consider how the criteria themselves apply to the area of data mining which has few assignments proposed. Finally, we will consider whether the basis of this assignment, the use of Open Data as a source of data to analyse, can be extended to different cases and examples, and if so how. Keyword : Nifty assignments; Open Data; Business Intelligence; Computer Science Education

Item Type: Book Section
Research Institute, Centre or Group: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Depositing User: Charles Boisvert
Date Deposited: 18 May 2016 11:34
Last Modified: 27 Oct 2016 21:20

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