Integrated data management and business performances
Abstract
This editorial objective is to contribute to the debate on new approaches to corporate data management for the improvement not only of management control systems, but also of the related corporate performance. The theme of integrated data management embraces the interdisciplinary relationships that management controls — and the accounting function — should increasingly have with other disciplines; these relationships are permeated by both quantitative and qualitative approaches. Quantitative models include those created through data science and those that refer to mathematics, statistics, and information technology.
Business models of data management combine qualitative and quantitative approaches. Furthermore, when dealing with other disciplines this models have to deal not only with “data management”, but also with knowledge management, and this often creates barriers for diversity of scientific approach of the different branches of knowledge. Lastly, it should be reiterated that the data processing analyses involve not only internal data (accounting and non-accounting), but also external data, of a statistical, economic, and social nature, which affect the integrated management of accounting data from different disciplinary perspectives. Moreover, the data processing analysis also concern big data.
Keywords: Data management; Quantitative models; Data science; Knowledge management; Big data; Decision-making processes; Blockchain; Internet of things
