AI Natural Language Query

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Auto Repair Dataset

You own a busy auto repair shop with a team of technicians. You service a variety of vehicles — from oil changes and brake jobs to engine diagnostics and transmission work. You track customers, their vehicles, work orders with labor and parts costs, and technician assignments. You have 18 months of service history. Use natural language to analyze revenue, technician productivity, common repairs, and customer retention.

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Available Data
📅 Mar 2024 through Mar 2026
Tables: shop_customers, vehicles, work_orders

Customers — name, email, phone, first_visit
Vehicles — customer → shop_customers, make, model, year, mileage
Work Orders — vehicle → vehicles, date_in, date_out, service_type (Oil Change/Brake Service/Tire Service/Engine Diagnostic/Transmission/Electrical/AC & Heating/General Maintenance), description, labor_cost, parts_cost, total_invoice, status (completed/in-progress/waiting-parts), technician

Relationships: Vehicles belong to Customers. Work Orders reference Vehicles.