MATCHING of PROCESS DATA and OPERATIONAL DATA for a DEEP BUSINESS ANALYSIS. ONTOLOGY DESIGN for POSSIBLE MATCHING and RECOMMENDATIONS to IMPROVE it?

Companies have long been taking the assistance of only the operational data of a business process, when analyst make their decisions just on the basis of operational data but the pitfall of this method was that context of the business process was missing therefore decisions made in the light of such analysis were not up-to-date and sometimes inaccurate because decision made just on the basis of operational data with the exclusion contextual information ultimately effects the decision making process. Therefore, amalgamation of these two data sources is the need of time, consolidation of the operational data (needed to perform business procedures, processes and collected during the operational implementation of an operational process) and business process data (consists of a set of activities that are executed in some enterprise or administration according to some rules in order to achieve certain goals) is inevitable. With this convergence evaluation and the decision making result will be more valuable and will result in the form of deep business analysis. How this convergence can be done seamlessly automatically considerable by the any system that can perform deep business analysis? Its answer ultimately needs for the design of ontology for the possible matching of the process data and operational data for a deep business analysis so that the recommendations impeccably automatically available for any analysis system, data mining or any business intelligence tool. Deliverable of this research will be an ontology, however to develop ontology we have selected different database management system tools and process management system tools to collect event log of operational data and process log respectively.