A Multi-Agent Framework for Data Extraction,Transformation and Loading in Data Warehouse
Ramzan Talib, Muhammad Kashif, Fakeeha Fatima, Shaeela Ayesha · International Journal of Advanced Computer Science and Applications · 2016
The rapid growth in size of data sets poses chal-lenge to extract and analyze information in timely manner for better prediction and decision making. Data warehouse is the solution for strategic decision making. Data warehouse serves as a repository to store historical and current data. Extraction, Transformation and Loading (ETL) process gather data from different sources and integrate it into data warehouse. This paper proposes a multi-agent framework that enhance the efficiency of ETL process. Agents perform specific task assigned to them. The identification of errors at different stages of ETL process become easy. This was difficult and time consuming in traditional ETL process. Multi-agent framework identify data sources, extract, integrate, transform, and load data into data warehouse. A monitoring agent remains active during this process and generate alerts if there is issue at any stage.