Tacit knowledge for business intelligence framework: A part of unstructured data? - Surbakti, Herison (JATIT & LLS. All rights reserved., 2018)
Idea to capture knowledge from different sources can be very beneficial to Business Intelligence (BI). Organizations need to collect data sources from type of structured and unstructured, including individuals' tacit knowledge in order to have the better output in data analysis. Therefore, the complexity of BI processes need to be explored in order to ensure the process will properly treat the tacit knowledge as a part of the data source in BI framework. Moreover, the linkage between unstructured data and tacit knowledge is generally consistent, for the reason that one of tacit knowledge characteristic is unstructured, which is difficult to capture, codify, estimate, investigate, formalize, write down, and communicate accurately. Cognitive approach is ideally suited for the capturing tacit knowledge as from among the massive data available these days. Typically, the organization must integrate multiple streams of data from several sources or other collaboration resources with the knowledge systems for making the decisions. This paper explores the possibility of tacit knowledge used in BI framework to perform data analysis for decision makers