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Garage Management System: Expanded Scenario and Data Joe's Garage is a bustling family - owned business operating in Pretoria, South Africa, for over 2 0

Garage Management System: Expanded Scenario and Data
Joe's Garage is a bustling family-owned business operating in Pretoria, South Africa, for over 20 years.
They cater to a diverse clientele, from individual car owners to corporate fleets. However, their aging
Excel system struggles to manage:
Growing customer base: Over 2,000 customers with varying vehicle types and service histories.
Complex service offerings: Including routine maintenance, repairs, diagnostics, performance
upgrades, and tire services.
Expanding inventory: Parts, tools, and consumables across various brands and categories.
Multiple employees: Mechanics, technicians, service advisors, and administrative staff with
varying roles and permissions.
Financial tracking: Invoicing, payments, accounts payable/receivable, and payroll management.
Data Expansion:
Customers: Include loyalty programs, contact preferences, vehicle purchase history, and service
preferences.
Vehicles: Add VIN numbers, model years, mileage, fuel types, and service records with dates,
descriptions, and costs.
Services: Expand with specific labor costs, parts used (linked to inventory), and warranty
information.
Invoices: Include payment methods, discounts, taxes, and technician assigned.
Inventory: Implement categories, suppliers, minimum/maximum stock levels, reorder points,
and purchase orders.
Employees: Include roles, departments, salaries, work schedules, and access control levels.
Database Design & Development:
1. Develop an Entity-Relationship Diagram (ERD) representing the entities mentioned in the
scenario and their relationships. Ensure it adheres to normalization principles.
2. Create tables in your chosen DBMS (e.g., MySQL) based on the ERD, defining appropriate data
types, constraints, primary/foreign keys, and relationships.
3. Populate the database with realistic dummy data covering customers, vehicles, services,
invoices, inventory (limited scope for this project), and employees (limited scope). Ensure the data represents the diverse clientele, service offerings, and employee roles outlined in the
scenario.
4. Develop code (e.g., Python with pandas) to read the Excel data, transform it if necessary, and
insert it into the database tables efficiently. Include error handling in your code.
Database Optimization:
1. Identify frequently used columns in queries and create indexes on them to improve query
performance. Use code (e.g., SQL queries) to create and manage indexes.
2. Evaluate the trade-offs between data redundancy and query performance for specific scenarios.
Justify any strategic denormalization you implement while maintaining data integrity. Use code
to implement the changes.
3. Analyze slow queries using tools like EXPLAIN PLAN. Use code (e.g., SQL queries) to rewrite
inefficient queries with techniques like joins optimization and subquery elimination.
Automation Tasks:
1. Implement automated data backups periodically (e.g., daily) using code (e.g., shell scripts) and
tools like mysqldump. Automate restoration scripts for potential disaster recovery.
2. Develop code (e.g., Python, SQL) to automatically generate invoices upon service completion
based on service and parts data. Integrate with payment gateways for automated billing.
3. Create triggers or stored procedures to track inventory levels and automatically generate
reorder points when stock falls below a threshold. Use code to automate purchase orders when
triggered.
Disaster Recovery:
1. Set up database replication to a secondary server for redundancy and failover in case of primary
server failure. Use code (e.g., mysqldump + scripts) to automate replication setup and
management.
2. Explore high availability (HA) solutions like clustering for further resilience. Research tools like
Galera Cluster or DRBD for MySQL clustering and discuss their feasibility.
3. Develop a comprehensive disaster recovery plan documenting steps to recover from various
scenarios (e.g., hardware failure, data corruption). Include database restoration, application
recovery, and data synchronization procedures.
Mark Allocation:
Database Design & Development:
ERD clarity, completeness, and adherence to normalization principles
Table structure, data types, constraints, and relationships
Dummy data realism, quantity, and coverage of entities
Data import code efficiency and error handling
Database Optimization :
Indexing strategy and impact on query performance
Denormalization justification and implementation (%)
Query optimization techniques and performance improvement
Automation Tasks:
Data backup & restore automation effectiveness and reliability
Invoice generation code functionality and integration
Inventory management triggers/procedures and purchase order automation
Disaster Recovery:
Replication setup and management using chosen tools
High availability considerations and potential solutions
Disaster recovery plan comprehensiveness and recovery procedures
please give me step by step coding on all of these

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