Project Synopsis:

In a significant endeavor to centralize data access for a multinational corporation with sprawling headquarters across Europe, I spearheaded the development of an enterprise data warehouse (EDW). The objective was to create a singular repository for all data analytics, offering uniform access to various company offices and their local IT departments. The technology stack chosen for this project included Microsoft SQL Server for the database management and SQL Server Integration Services (SSIS) for the integration and transformation tasks, linking the new data warehouse with the existing SAP R3 ERP system.

Project execution:

Requirement Analysis and Strategy Development: The first stage involved a meticulous requirement gathering process. Meetings with key stakeholders from each of the European headquarters were held to ensure the data warehouse design would meet the diverse needs of the entire organization. We developed a strategic blueprint that delineated how data from SAP R3 would flow into the data warehouse, ensuring data integrity, consistency, and accessibility.

Design and Architecture: With the blueprints approved, the design phase began. The architecture was tailored to support high volumes of data from multiple sources, focusing on scalability and performance to cater to the international operations. The warehouse schema was carefully designed to reflect the global business process, ensuring data from various ERP modules could be seamlessly integrated.

Development with MS SQL Server and SSIS: Utilizing MS SQL Server, I constructed the data warehouse infrastructure, setting up secure and optimized storage that would form the backbone of the company’s data analytics. SSIS played a crucial role in the development process as the primary tool for extracting, transforming, and loading (ETL) data from SAP R3 to the data warehouse. Complex SSIS packages were developed to automate the ETL processes, enabling efficient data consolidation and transformation to the unified format required for analytical purposes.

Testing and Quality Assurance: Comprehensive testing routines were initiated to ensure the integrity and reliability of the data within the warehouse. This involved rigorous data validation, performance testing, and ETL process verification. Particular emphasis was placed on ensuring that the ETL processes were robust and could handle the full data loads and subsequent updates without performance degradation.

Deployment and Training: The deployment phase was meticulously planned to minimize disruption to ongoing operations. A phased rollout allowed individual headquarters to migrate to the new system in a controlled manner. Training sessions and detailed documentation were provided to each local IT department, enabling them to utilize the data warehouse effectively. These efforts ensured a smooth transition and immediate operational efficiency gains post-deployment.

Project Outcome:

The resulting data warehouse became the definitive source of organizational data, providing consistent, reliable, and quick access to information across the entire company. It supported the decision-making processes with real-time data insights, enhancing the responsiveness of the multinational corporation to market changes and internal performance metrics.


The project was a milestone in the company’s data management strategy, setting a high standard for future data initiatives. It demonstrated my ability to navigate complex, large-scale data projects and underscored the potential of combining SQL Server and SSIS to create powerful data warehousing solutions tailored for international business needs.