Car manufacturers analyse the high volume of data each vehicle generates in many ways. It's not only the internal data, but the contextual data- external to the car.

Telematics record the speed of a vehicle at a point in time - say 30 mph. Looks safe but in the context of a traffic jam is dangerous. 90 mph sounds reckless unless it is on a free-flowing autobahn.

Combining traffic information and weather puts a different perspective on a vehicle's performance and driver's actions. Data from prototypes needs to be augmented by the unstructured comments of drivers and passengers.

Big Data platforms like IDOL lets auto manufacturers analyse video, image and audio data, structure and combine with telematics to gain the insights to make better vehicles, or components.

Combine that with feedback from the network of dealers to get an even more complete picture. As the volume and velocity of data increases adopt a columnar data platform like Vertica.

What's the good unless you can share insights with all people that need insights to make and execute better decisions. Embed Analytics as the visualisation, BI layer to analyse, visualise these insights.

60%-70% of users probably happy to use dashboards and reports with some customisation capabilities. Another 20% may want enhanced self-service abilities to query data, author dashboards and reports and publish these to enterprise reporting.

The other 10% maybe analysts that need data discovery tools to discover new insights and create new KPIs. In the past they needed work-group Analysts Tools but not today. 

On the one analytics platform, secure and scalable, these analysts can add self-service analytics without creating silos of insight.

Purpose built data analytics for car manufacturers to gain and keep that competitive edge.