Abstract:

Nowadays, the data from various source systems lies in different formats. To make data suitable for strategic decisions, we need an extract, transform and load (ETL) software to extract data from various resources and to transform them into required data formats and then load it into the data warehouse. In this paper, we have designed a new approach called DTEL (m, k)-firm-RTDW (Decentralized Extract Transform Load approach based on (m, k)-firm constraint for Real-Time Data Warehouse) which enables to deal with diversity and disparities in data source systems and thus to reduce the time for ETL considerably and to provide real-time data continuous integration loading. Experimental results show that our approach performs better than the conventional FCSA-RTDW (Feedback Control Scheduling Architecture for Real-Time Data Warehouse) using the new TPC-DS benchmark.