Automotive market big data project

Quantitative decision making in the world of cars

Use cases

• Private buyers and vehicle owners

• Dealers working on inventory procurement

• Insurance agents estimating vehicle value

• Market researchers

What does it do?

• Aggregates the entire Canadian automotive market

  • Minimal update latency
  • Over 10 million vehicles in historical data

• Offers simple live market view

• Looks for patterns

  • Flags vehicles with invalid data
  • Tags based on keyword analysis (e.g. passed inspection, new tires, one owner)
  • Creates Value Indexes for each model

• Estimates vehicles' values
  • Contaminated data excluded from index calculations
  • Indexes account for seasonal and other price fluctuations

Additional Features

• Dealer market and Private market differentiation

  

• Vehicle’s depreciation estimation with respect to age and mileage

• Business intelligence (complete view of any dealership)

  

Technology Used

• Python 3.7
• Django
• MongoDB