Enhancing the QoS of a Data Warehouse through an Improved ETL Approach

Abstract

This study aims at developing a data warehouse with enhanced security and Quality of Service (QOS) by enriching the Extract Transform Load (ETL) process.  Existing Data warehouse models, which include the Relational core model, the Dimensional core model, and the Data Vault Model fail to either adequately address user requirement, perform ad-hoc queries, or require vast amounts of storage space and computational power. The proposed model addresses these challenges with Remote Sync (RSYNC) Utility to improve the performance of a data warehouse, Secure Shell (SSH) protocols to enhance security, and the nearest neighbor approach for more flexible data extraction and loading process. The research used an experimental design to implement a prototype and data collected by simulating laboratory experiments. When compared to the traditional models, the enhanced model improved Extraction by enhancing the flexibility of ad-hoc queries, introducing host-based Authentication, and reducing the data transmitted between the source and destination.

Key words: data, warehouse, remote, sync, quality, ETL, secure, shell