Tommi Holmgren developed a unified Multi-source Data Access Template for the Sema4AI/actions repository, enabling seamless integration of both file-based and PostgreSQL data sources. Using Python and SQL, Tommi designed the template to support flexible data queries, such as retrieving customer information by country and calculating monthly sales per company. The work included example queries, configuration files, and sample data to streamline onboarding and accelerate analytics workflows for other teams. By focusing on template development and data engineering, Tommi established a reusable foundation for cross-source data access, improving query flexibility and setting a pattern for future data integration efforts.