PostgreSQL Database Design ETL Pipeline
I utilized advanced SQL techniques, including primary/foreign key relationships and complex joins to ensure data integrity—applying a clinical-grade precision to retail data sets.
I architected a 3rd Normal Form (3NF) relational database using PostgreSQL. This involved mapping out an Entity Relationship Diagram (ERD) to eliminate data redundancy across seven core tables: Customers, Orders, Products, Categories, Suppliers, Inventory, and Order_Items. By implementing referential integrity constraints and optimized indexing, I created a system capable of handling complex analytical queries, such as calculating month-over-month growth and individual Customer Lifetime Value via SQL window functions.
Data Science is only as effective as the infrastructure that supports it. This project proves my ability to provide "end-to-end visibility" into the data lifecycle. By building a robust relational model, I ensure that the data fed into predictive models is accurate, structured, and consistent. In a business context, this architecture provides a single source of truth, enabling executives to make real-time decisions regarding inventory management and high-value customer retention strategies.
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