Enhancing Data Warehouses Security

Abstract

Data Warehouses (DWs) are essential for enterprises, containing valuable business information and thus becoming prime targets for internal and external attacks. Data warehouses are crucial assets for organizations, serving critical purposes in business and decision-making. They consolidate data from diverse sources, making it easier for organizations to analyze and derive insights from their data. However, as data is moved from one source to another, security issues arise. Unfortunately, current data security solutions often fail in DW environments due to resource-intensive processes, increased query response times, and frequent false positive alarms. The structure of the data warehouse is designed to facilitate efficient analysis. Developing and deploying a data warehouse is a difficult process and its security is an even greater concern. This study provides a comprehensive review of existing data security methods, emphasizing their implementation challenges in DW environments. Our analysis highlights the limitations of these solutions, particularly in meeting scalability and performance needs. We conclude that current methods are impractical for DW systems and support for a comprehensive solution tailored to their specific requirements. Our findings underscore the ongoing significance of data warehouse security in industrial projects, necessitating further research to address remaining challenges and unanswered questions.