A Near Real-Time Data Warehouse Architecture Based on Ontology

Data warehouse does not provide external data that are required to dynamically build after design and create the data warehouse. Therefore, analysts conduct effective analysis to find a correlation between external data and data warehouse data, and in other cases requires a comparison both external data and data warehouse data together. The analyst forced to repeat some past repetitive situations. This includes creating terminology, measures and comparison. In this paper, for graduates of this problem, a real-time data warehouse architecture based on ontology is proposed. Furthermore, an algorithm to reduce the response time to users’ queries using materialized views and parallel processing is proposed. A case study to demonstrate how to create correlation between external data and data warehouse data is done and the results show the correlation between external data and data warehouse data is discovered. In experiments, using both direct and parent materialized views approaches in existing data warehouse architecture, reduce response time to users’ sequential, comparative and combination queries.