Project Overview
In this project, I designed and built a data warehouse for nutrition data analysis, integrating information from multiple sources to enable efficient reporting and decision-making. Using SQL Server Integration Services (SSIS), I extracted, transformed, and loaded (ETL) data from SQL Server, Excel, and Microsoft Access, ensuring clean, structured, and unified data storage for analysis.
This centralized warehouse provides a single source of truth for nutrition-related data, allowing stakeholders to analyze trends, resource allocation, and program effectiveness in supporting public health initiatives.
Data Warehouse Design & Implementation
Designed and implemented a star schema data warehouse specifically optimized for analytical queries, ensuring efficient storage and retrieval of nutrition data. This involved structuring the data into fact and dimension tables, where fact tables contained key transactional data and dimension tables provided contextual details, enabling easy aggregation and trend analysis.
To enhance query performance and data retrieval speed, I carefully defined relationships between tables, ensuring referential integrity through primary and foreign keys. Additionally, I optimized the database by implementing indexing strategies, partitioning large tables, and tuning queries to handle large datasets efficiently. This well-structured data warehouse provided a scalable and high-performing environment for analyzing nutrition data across different programs and geographies.
