business intelligence, data minimization, linguistic variables, ETL process, expert system, ERP, data source

The paper proposes a new approach of data warehouse minimization by fuzzy-based ETL filter for ETL processes in business intelligence (BI) systems. First part introduces common company systems and possible data sources in the company. Second part states the problem with interpreting information in BI systems and explains a data representation in the BI systems. Third part of the paper identifies suitable linguistic variables that help with interpreting the data to the user and automated filter as well. We also define a rule base and input and output values of expert system. Last part of the paper proposes a two ways to minimize a data - modification border of the fuzzy set and omitting useless combinations of the linguistic variables and modifiers.