Multidimensional information systems metadata repository development with a data warehouse structure using “data vault” methodology

When organizing automated data collection in a data warehouse under the conditions of increasing data volume and complicating the business model of an enterprise, an information system data model control becomes one of the priority tasks. The article discusses a method of metadata repository developing in terms of metadata responsible for describing business objects and the relationships between them. The choice of “Data vault” determines the construction of a data warehouse within the framework of an information system based on the classical design approach with a 3-level data presentation architecture, which includes a data preparation area, or an online data warehouse, data warehouse and thematic data marts. The proposed approach allows organizing data storage within the data warehouse using a metadata repository based on the multidimensional organization principle. The metadata repository is responsible for the data collection process, the data storage process, and the presentation of data for analysis. The metadata repository is presented in the form of a metamodel that is semantically related to the domain of the system, is easily reconstructed in case of changes in the business model of the domain, and allows data marts to be created with the structure of a multidimensional data model based on the Star relational scheme. This allows you to organize the human-computer interaction when describing a metamodel, using mainly knowledge about the structure of the subject area. When describing a metamodel, the first-order predicate calculus language is used, which makes it possible to control the metamodel using a declarative programming style - the “Prolog” language. The key point in the structure of the information system is the way of transition from the “Data vault” model to a multidimensional data representation model based on associative rules of dependence between information objects. © 2019 Association for Computing Machinery.

Kuznetcov Y.1 , Fomin M. 2 , Vinogradov A. 3
Сборник материалов конференции
Association for Computing Machinery
  • 1 Department of Digital Solutions, KSN Technology Company, Moscow, Russian Federation
  • 2 Department of Information Technology, Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 3 Artificial Intelligence Research Center, Ailamazyan Program Systems Institute of RAS (PSI RAS), Pereslavl-Zalessky, Russian Federation
Ключевые слова
Data mart; Data vault; Data warehouse; Multidimensional data model; OLAP
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