International Journal of Science, Engineering and TechnologyAuthors: Zubair Khan
Abstract: The growing complexity of enterprise data ecosystems has elevated the role of Extract, Transform, and Load (ETL) processes in ensuring reliable, timely, and high-quality information for decision-making. SQL Server Integration Services (SSIS), as Microsoft’s flagship ETL platform, provides a comprehensive framework for data integration, transformation, and quality management. This review explores the evolution of ETL, the architecture and core components of SSIS, and its practical applications across industries such as retail, healthcare, finance, and cloud-based environments. By examining best practices, data quality strategies, and governance frameworks, the study highlights how organizations can optimize SSIS packages for efficiency and reliability. Comparative analysis with competing platforms such as Informatica, Talend, and cloud-native services reveals both the strengths and limitations of SSIS, particularly in scalability and hybrid integration. Furthermore, future trends such as AI-driven automation, serverless ETL models, and cloud-native architectures are evaluated to understand the evolving role of SSIS in modern data ecosystems. This review concludes that while SSIS faces challenges in distributed and multi-cloud contexts, it remains a powerful and cost-effective solution for enterprises aligned with Microsoft technologies, capable of bridging legacy infrastructures with next-generation data platforms.
DOI: https://doi.org/10.5281/zenodo.17276968
