- Title
- An Agile group aware process beyond CRISP-DM: A hospital data mining case study
- Creator
- Sharma, Vishakha; Stranieri, Andrew; Ugon, Julien; Martin, Laura
- Date
- 2017
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/180837
- Identifier
- vital:15837
- Identifier
-
https://doi.org/10.1145/3093241.3093273
- Identifier
- ISBN:9781450352413
- Abstract
- The CRISP-DM methodology is commonly used in data analytics exercises within an organisation to provide system and structure to data mining processes. However, in providing a rigorous framework, CRISP-DM overlooks two facets of data analytics in organisational contexts; data mining exercises are far more agile and subject to change than presumed in CRISP-DM and central decisions regarding the interpretation of patterns discovered and the direction of analytics exercises are typically not made by individuals but by committees or groups within an organisation. The current study provides a case study of data mining in a hospital setting and suggests how the agile nature of an analytics exercise and the group reasoning inherent in key decisions can be accommodated within a CRISP-DM methodology.
- Publisher
- Association for Computing Machinery
- Relation
- ICCDA '17: Proceedings of the International Conference on Computer and Data Analysis May 2017 p. 109-113
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- © 2017 Association for Computing Machinery.
- Subject
- Reasoning Community; Agile Data Mining; CRISP; Health Analytics
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