The process of turning data into knowledge is referred to as “knowledge discovery” (KD) and originated in the 1990s. Since that time many different process models and methodologies have been developed. A genealogy presented in 2010, showed how the different models evolved and presented a refined process model, which represents a synthesis of the models presented before. However, the rise of data analytics and big data have changed how organizations do business. The key to these changes is to use data and turn it into knowledge to create value for the organization. Therefore, this study aims to update our understanding of knowledge discovery processes by reviewing the research into KD processes since 2010 in order to understand if there have been considerable changes and developments in this field. The developments in KD process models and methodologies that were found are threefold: tasks, steps and agile practices.
|Title of host publication||Proceedings of the 25th Americas Conference on Information Systems (AMCIS)|
|Publisher||AIS Electronic Library|
|Number of pages||10|
|Publication status||Published - 2019|
|Event||25th Americas Conference on Information Systems: New Frontiers in Digital Convergence - Cancún, Mexico|
Duration: 15 Aug 2019 → 17 Aug 2019
|Conference||25th Americas Conference on Information Systems|
|Abbreviated title||AMCIS 2019|
|Period||15/08/19 → 17/08/19|
- data science process
- knowledge discovery
- literature review
Baijens, J., & Helms, R. W. (2019). Developments in knowledge discovery processes and methodologies: Anything new? In Proceedings of the 25th Americas Conference on Information Systems (AMCIS) (pp. 1-10). AIS Electronic Library.