Case Study: #1 - The Big Data Challenges

Arnechia Washington
Professor Durgin
CIS500 Info Syst Decision-Making
January 26, 2014

Volvo Car Corporation has incorporated the cloud infrastructure into its networks to globalize the company. “With hundreds of sensors and CPUs embedded throughout the car — from the brakes to the central locking system — data is now being captured for use within the vehicle itself, and also, increasingly, for transmission via the cloud back to the manufacturer” (Strader, 2011). Volvo’s data Warehouse has multi-terabytes of data from the hundreds of sensors and CPU’s that are embedded throughout the car as well as data from customer relationship systems. The Cloud platform allows implementing and evaluating real-time information systems to transform data into knowledge. This will give Volvo a competitive advantage over other car companies and allow their offices no matter the location to immediately take advantage of the data that is stored.
There are two different cloud infrastructures within their infrastructure: service cloud and vendor hosting. Service cloud is used to support the customers and while their customers are operating the vehicles. This will enhance the car from the information that is gained based on the design and performance level of the car. Vendor hosting is used for the data that is located in separate warehouses. This platform allows the data to be consolidated into one place and reduces the cost to maintain, operate or license their own warehouses. “By splicing that data together, we are pre-warned about potential issues such as mechanical problems that might have shown up later in the field” (Strader, 2011). Collaboration is essentially gained from clouding. So many new developments and improvements have been from clouding. Volvo made a cost-effective choice as well as a wise choice. Knowledge is power and having endless access to data that allows you to produce a quality product is even more powerful. “At Volvo, a system from data warehousing company Teradata integrates product configuration, warranty and vehicle diagnostic data to support technical and business analysis throughout the product lifecycle” (“Teradata Case Study”, 2012) . The developers and programmers use the data produced by vehicles to directly outline the design and production of those still on assembly lines and CAD screens. Also faults can be improved from the information that is collected by analyzing the data from sensors and onboard computers. As well as developing the most effective maintenance plan for their vehicles because they know when specific components need to be checked or replaced. By integrating the data into a Teradata Warehouse standard reports and provisional analytics could be performed and applied by using Business Intelligence (BI) tools and in-house developed applications. The increase in the storage in 2007 to 1.7 terabytes improved response times dramatically. This quick calculation allowed the new environment to run daily fleet mileage in five minutes which normally took two hours. Also, the time to create comprehensive reports of diagnostic failure codes by year and model was reduced from two weeks to 15 minutes. The Big Data strategy gives Volvo Car Corporation a competitive advantage because the “…large-scale data capture and analysis is driving improvements in safety” (“Teradata Case Study”, 2012). Their vehicles have rated among the safest and a lot of that, I think, is their ability to review safety and system data that is collected from their vehicles. Due to having all that information available because of real time analytics is the key to Volvo Car Corporation’s success. “Volvo Car Corporation is the automotive industry's leader in safety and our engineers are now developing next-generation technologies as another step toward our vision that nobody should suffer fatal or serious injuries in a new Volvo car by the year 2020" (“Volvo”, n.d.). In order to fulfill this vision, Volvo Car Corporation has implemented data collected from vehicles before and after car crashes to enhance the safety of their vehicles. They have improved their seat belts, the three-point safety belt is the tool that has saved the most lives and is considered to be the single most important safety solution in the history of the automobile. Pedestrian Detection with full auto brake was developed as well from the Big Data. This feature uniquely detects and activates full braking power if the driver does not react to the danger of a pedestrian stepping out in front of the car. Another important feature to me is the alcohol lock called Alcoguard, which prevents drivers under the influences from driving. In Sweden, Alcoguard requests to register a blood-alcohol limit of less than 0.2 g/l before it directs a radio indicator to start the car. People choose a car with their hearts and Volvo has won the hearts of America. Volvo has definitely taken the car corporation to a higher level with implementing Big Data into their inventions and designs. The voluminous amount of data may have been overwhelming and costly to store but the cost to purchase high volume storage has earned them tremendous respect in the auto industry. They have very safe vehicles and amazing features. The real time data processing gives them the edge needed to produce safe vehicles and remain competitive.

References
Blanco, B (September 2007). Volvo's fuel cell Alcoguard breathalyzer says "Blow 5 seconds". Retrieved from http://green.autoblog.com/2007/09/03/volvos-fuel-cell-alcoguard-breathalyzer-says-blow-5-seconds/
Strader, R (January 2011). Converting data into business value at Volvo. Retrieved from https://blackboard.strayer.edu/bbcswebdav/institution/CIS/500/1124/Week3-1124/CIS500CaseStudy1-Volvo.pdf
Teradata case study: A car company powered by data. (2012, May 16). Retrieved from http://www.thebigdatainsightgroup.com/site/article/teradata-case-study-car-company-powered-data
“Volvo. In a demonstration of continued leadership in the field of safety, Volvo Car Corporation establishes new test facility for active car safety” (n.d.). Retrieved from http://www.autoalliance.org/index.cfm?objectid=02000880-B49C-11E1-B12B000C296BA163