Improvement of the Analytical Queries Response Time in Real-Time Data Warehouse using Materialized Views Concatenation

A real-time data warehouse is a collection of recent and hierarchical data that is used for managers’ decision-making by creating online analytical queries. The volume of data collected from data sources and entered into the real-time data warehouse is constantly increasing. Moreover, as the volume of input data to the real time data warehouse increases, the interference between online loading operations and online analytical processing increases. These two stated challenges have become the most important issues regarding real time data warehouse. In this article, a method is presented to improve the analytical queries response time in the real time data warehouse architecture using materialized views concatenation. This process takes place by: (1) storing the results of performed queries in each real time section, (2) transferring the results to the next section when transferring data to the section. Each real time section contains data of its previous section, which have been transferred in several stages. As a result, the calculated results of the queries are also transmitted by transferring data, and consequently, for achieving desired outcome, the previously calculated results can be combined without the need to run the queries again. The proposed method has reduced both analytical queries response time and data entry interference caused by the simultaneous and long-term execution of queries. This study faces two challenges: (1) applying the proposed method to a small amount of data in the real time section and (2) the changes in the proposed method for applying to big data.