Cars are rolling gold mines of information, gathering data about the driver, the driving environment and, of course, the car itself as well as any connected devices. Automakers can use this data to enrich the driving or service experience, improve safety and enhance vehicle quality.
The benefits of the connected car extend beyond just the automotive industry. Insurance companies can more accurately assess risky driver behavior, enhance the claims process and identify fraudulent claims. Fleet operators as well can improve the efficiency and safety of their operators.
But automakers have been capturing telematics information for years. What’s happening now that has generated this renewed interest?
A big part of the answer lies in the maturation of big data and analytics technology. Automakers now have the ability to analyze huge volumes of vehicle data at speeds that allow cars to “talk” to each other through the cloud and let their drivers connect with each other in real-time and send alerts about nearby hazardous road conditions.
In our next Twitter chat, guest Michael Cavaretta, Ph.D., technical leader, predictive analytics/data science Ford Motor Company, joins us as we discuss “When cars talk.” Here are the questions we’ll be discussing as well as reference articles to help inspire the upcoming January 29th discussion, at 12 p.m. ET. Don't miss this!
#BigDataMgmt Chat Discussion Questions
- How can telematics data from one vehicle be used to warn drivers in other vehicles about potential road hazards?
- How can analyzing data collected from cars help diagnose quality problems faster?
- Can information collected from vehicles be combined with service records, warranty systems, ERP systems and more? How?
- How can component failure/excessive wear be correlated with driving patterns?
- How can component failure information be correlated with data about the environment where the failure occurred?
- How can timely alerts or warnings be sent to drivers in real time without distracting them?
- Where are we going to store all this “car chatter?"
How are talking cars changing the way people move?
#BigDataMgmt Chat Reference Articles
- Leading Through Connections: Insights from IBM Global CEO Study
- How great companies innovate
- Big Data Drives Product Innovation - Data Management
#BigDataMgmt Chat Guest Bio:
Michael Cavaretta is technical leader of predictive analytics for Ford Motor Co., Dearborn, MI. He was hired by Ford 15 years ago while he was working as a consultant for Churchill Systems doing data mining and statistical analysis. Cavaretta has led multiple data and analytics projects at Ford to break down silos inside the company to best define Ford’s most fruitful datasets. Ford has successfully aggregated customer feedback, and extracted all the internal data to best predict how new features and technologies will improve their cars. He holds a PhD in computer science, with an emphasis on artificial intelligence, from Wayne State University in Detroit.
Tom Deutsch serves as a Program Director on IBM’s big data team. He played a formative role in the transition of Hadoop-based technology from IBM Research to IBM Software Group, and he continues to be involved with IBM Research big data activities and transition from Research to commercial products. Tom created the IBM BigInsights Hadoop-based product, and has spent several years helping customers with Apache Hadoop, BigInsights and Streams technologies, identifying architecture fit, developing business strategies and managing early stage projects across more than 200 customer engagements. He also co-authored the popular book “Understanding Big Data,” as well as many other papers.
As IBM's big data evangelist, James Kobielus is IBM Senior Program Director, Product Marketing, Big Data Analytics solutions. He is an industry veteran, a popular speaker and social media participant and a thought leader in big data, Hadoop, enterprise data warehousing, advanced analytics, business intelligence, data management and next best action technologies.