Advanced SQL, Oracle PL/SQL, and PostgreSQL PL/pgSQL University Course Project 📘

Overview 🏫

This repository contains projects developed during a university course on advanced and in-depth SQL, Oracle PL/SQL, and PostgreSQL PL/pgSQL. Each phase of the project builds upon the previous, exploring different aspects of database management, data processing, and query optimization.

Repository Structure 📁

• Phase1/: Data Generation
• Phase2/: Implementation of Complex Integrity Constraints
• Phase3/: Otter Lineage Tracing in PL/SQL
• Phase4/: SQL Query Optimization and Analysis
• Phase5/: Data Processing and Audit in PostgreSQL
• README.md: Main README file for the repository.

Technology Stack and Concepts 🔧

• Languages and Frameworks:

  • Oracle PL/SQL
  • PostgreSQL PL/pgSQL
  • Docker for PostgreSQL server setup

• Key Concepts:

  • Procedures, Functions, and Packages
  • Anonymous Blocks
  • Triggers
  • Recursive Queries and Common Table Expressions (CTEs)
  • Data Preprocessing and Validation
  • Indexing and Query Optimization
  • Data Integrity and Constraint Management
  • Data Loading and Exporting
  • Audit Report Generation

Phase Descriptions 📜

1. Data Generation 📑

Objective: Generate realistic data for tbl_CLIENT, tbl_PAYMENT, and tbl_SERVICE tables using Oracle PL/SQL. Key Elements:

• Dynamic table drop and creation scripts.
• Procedures for populating tables with synthetic data.

Reflections and Learnings 🌟

• This phase involved understanding the data generation process, ensuring data integrity, and effectively using PL/SQL procedures for bulk data operations.

2. Implementation of Complex Integrity Constraints 🛠️

Objective: Manage data integrity and implement business logic using PL/SQL packages and triggers. Key Elements:

• Package pkg_iFix_management for advanced CRUD operations.
• Trigger trg_CheckServiceCostLimit to enforce financial constraints based on client privilege levels.

Reflections and Learnings 🌟

• This phase highlighted the power of PL/SQL in managing complex business rules and maintaining data integrity through procedural logic and triggers.

3. Otter Lineage Tracing in PL/SQL 🦦

Objective: Trace the lineage of otters using recursive queries in PL/SQL. Key Elements:

• Recursive Common Table Expressions (CTEs) to retrieve and display otter lineage.
• Procedures and scripts for table creation, data insertion, and lineage tracing.

Reflections and Learnings 🌟

• This phase provided practical experience with recursive queries and CTEs, showcasing their effectiveness in handling hierarchical data.

4. SQL Query Optimization and Analysis 🛠️

Objective: Optimize and analyze SQL queries within the Oracle database environment. Key Elements:

• Execution plan analysis and query refactoring.
• Implementation of indexing, join optimization, and parallel execution.

Reflections and Learnings 🌟

• This phase deepened understanding of SQL performance tuning, emphasizing the importance of efficient query design and execution plan analysis.

5. Data Processing and Audit in PostgreSQL 🛠️

Objective: Process and audit data within PostgreSQL, generating reports and ensuring data integrity. Key Elements:

• Data loading procedure load_csv_data for importing data from CSV files.
• Audit report generation procedure save_csv_audit for exporting monthly audit data.

Reflections and Learnings 🌟

• This phase demonstrated the complete data processing and auditing workflow within a PostgreSQL environment, highlighting practical applications for real-world data management.

Conclusion 📝

This repository encapsulates a comprehensive learning journey through advanced database management, focusing on both Oracle PL/SQL and PostgreSQL PL/pgSQL. The projects demonstrate practical applications of complex SQL concepts, recursive queries, data integrity management, and performance optimization.