Applying ETL fuzzy filter for data warehouse size minimization
Jaroslav Žáček, František Huňka · AIP conference proceedings · 2015
The paper proposes a new approach of data warehouse minimization by fuzzy-based ETL filter for ETL processes in business intelligence (BI) systems and discusses possibilities to tune up the process. 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 defines a rule base and input and output values of the 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.