Automobile manufacturing industry is an ever-developing industry driven to satisfy consumer's needs focusing on key factors like performance, comfort, luxury, eco-friendliness and most importantly driver and passenger safety. Driver profiling in modern times is a decisive and convenient method ensuing driver and passenger safety. This paper offers a knowledge base outline to the consumer for On-Board Diagnostics (OBD) and Driver Profiling. On-Board Diagnostics assists the user in car maintenance by enlisting Diagnostic Trouble Codes (DTC) from the car's Engine Control Unit (ECU) using an Android application. The second aspect of this paper, i.e. to profile the driver's behaviour is proposed in two different approaches, offering mathematical, visual and analytical analysis of consumer's driving behaviour. A simple, immediate and cost-effective approach to profile driver behaviours using GPS co-ordinates is accessible on the same Android application proposed for On-Board diagnostics. An alternate detailed, novel approach to profile driver behaviour is based on car engine parameters such as Engine speed/rpm, Vehicular Speed, Engine load & Throttle valve; is modeled using Data Analytics & unsupervised Machine Learning techniques.