Business Process and Organizational Data Quality Model (BPODQM) for Integrated Process and Data Mining.

Data Quality (DQ) is a key element in any Data Science project to guarantee that its results provide consistent and reliable information. Both process mining and data mining, as part of Data Science, operate over large sets of data from the organization, carrying out the analysis effort. In the first case, data represent the daily execution of business processes (BPs) in the organization, such as sales process or health process, and in the second case, they correspond to organizational data regarding the organization’s domain such as clients, sales, patients, among others. This separate view on the data prevents organizations from having a complete view of their daily operation and corresponding evaluation, probably hiding useful information to improve their processes. Although there are several DQ approaches and models for organizational data, and a few DQ proposals for business process data, none of them takes an integrated view over process and organizational data. In this paper we present a quality model named Business Process and Organizational Data Quality Model (BPODQM) defining specific dimensions, factors and metrics for quality evaluation of integrated process and organizational data, in order to detect key issues in datasets used for process and data mining efforts.