One of the most critical issues to be faced when building integration solutions in the field of integrated automation of business-processes of an enterprise is the problem of managing the so-called master data. Master data management is a set of processes and tools for the ongoing definition and management of company core data (including reference data). You can come across another name - reference data management [1]. Master data is data with the most important information for running a business: about customers, products, services, personnel, technology, materials, and so on. They are relatively rarely changed and are not transactional [2]. The purpose of master data management is to ensure that there are no repetitive, incomplete, inconsistent data in various areas of the organization's activities. An example of poor basic data management is the work of a bank with a client who already uses a loan product, but still receives offers to take such a loan. The reason for the misbehavior is the lack of current customer data in the customer service department. The basic data management approach envisages such processes as data collection, accumulation, data cleansing, their comparison, consolidation, quality control and data distribution in the organization, ensuring their subsequent consistency and control of use in various operational and analytical applications. (C) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 9th Annual International Conference on Biologically Inspired Cognitive Architectures.
