Data consumers need a "data supermarket," whereby all data, regardless of source, format, or volume, is easily accessible; what they need is data virtualization. Data virtualization forms a virtual data layer, just like a supermarket, that lies between the data sources and the consuming applications. Instead of working with copies of the data itself, data virtualization works only with the metadata (the information needed to access each source) in a virtual data layer. In an increasingly data-driven world, fast access to data is key for making real-time business decisions, so why waste precious time, money, and resources using outdated data integration tools, when you can "shop" with ease using data virtualization?
As the Internet of Things (IoT) revs up the automotive industry, connected cars are becoming "devices on wheels" with in-vehicle systems connected to the Internet. Therefore, car manufacturers must develop new services and applications to provide consumers with more personalized driving options. Collecting and analyzing this data will help carmakers understand user preferences, develop new applications, and give consumers a wider, more personalized range of driving choices. To get new automotive IT services to market quickly, carmakers may wish to partner with application developers, IT security companies, and enterprise companies with established cloud-based infrastructures and data analysis experience.
Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. As I look ahead at where market and technology is headed for 2017 and beyond, I am excited about several trends. The key theme across them is one of interconnection.