A Framework for Improving Data Quality in Data Warehouse: A Case Study

Abstract

Nowadays, the development of data warehouses shows the importance of data quality in business success. Data warehouse projects fail for many reasons, one of which is the low quality of data. High-quality data achievement in data warehouses is a persistent challenge. Data cleaning aims at finding, correcting data errors and inconsistencies. This paper presents a general framework for the implementation of data cleaning according to the scientific principles followed in the data warehouse field, where the framework offers guidelines that define and facilitate the implementation of the data cleaning process to the enterprises interested in the data warehouse field. The research methodology used in this study is qualitative research, in which the data are collected through system analyst interviews. The study concluded that the low level of data quality is an obstacle to any progress in the implementation of modern technological projects, where data quality is a prerequisite for the success of its business, including the data warehouse.