Relational database project for an e-commerce system focused on clean schema design, normalization, and query performance. Currently in development with Oracle SQL / SQL Developer and a Python-based CRUD UI (planned).
Status: In progress — expected completion: Nov 2025
- Languages & Tools: Oracle SQL, SQL Developer
- Planned: Python (CRUD UI), Git/GitHub for version control
- Designed a relational schema with 10 tables and 50+ relationships
- Achieved 100% 3NF/BCNF; reduced redundancy by ~40%
- Executed and optimized 10+ advanced SQL queries (multi-joins, nested, aggregations)
→ ~30% query efficiency improvement in testing
- Relational data modeling (entities, relationships, keys, constraints)
- Normalization to 3NF/BCNF and integrity constraints (PK/FK, NOT NULL, CHECK)
- SQL DDL/DML, multi-table joins, nested queries, aggregations
- Query tuning basics (rewrites, selective predicates, avoiding unnecessary work)
- Python-based UI for CRUD (insert, query, update, delete)
- Migration scripts & seed data workflow
- (Planned) Indexing strategy, views/materialized views, and explain/trace-based tuning
- Implement Python UI for streamlined CRUD operations
- Add indexes/views to further improve read performance
- Build test dataset and benchmark suite for reproducible query timings
- Author developer docs (schema ERD, table dictionary, usage examples)
By the end of this project, I will demonstrate:
- Relational design excellence: rigorously normalized schema (3NF/BCNF) with clear keys and constraints
- Performance-minded SQL: effective multi-join/nested queries, measured efficiency gains
- Data access tooling: practical Python CRUD UI for non-SQL users
- Operational hygiene: migration scripts, seed data, and versioned SQL in Git/GitHub