Living On the Edge: Extracting Ultimate Value from Your IoT Data

insidebigdata | June 13, 2018

Living On the Edge: Extracting Ultimate Value from Your IoT Data
The Internet of Things (IoT) is steadily generating inconceivable amounts of data. According to Gartner, 8.4 billion things will be in use in 2017, up 31 percent from 2016. And analysts expect this number to reach 20.4 billion by 2020. By 2025, the IoT is projected to generate more than 2 zettabytes of data, says Machina Research. What does all that data mean? With streaming analytics, it can mean real-time reactions to events that can be lifesaving. For example, a truck receives data about an ice patch on the road. The truck then not only adjusts for the driver, but alerts other vehicles of the exact location of the ice. To make this kind of real-time information available with the high volume and velocity of data constantly streaming in from IoT sensors and network operations, you need a different type of data management solution than that is required for traditional, stationary transactional data. Take the truck example. Imagine that you’re driving a truck in Colorado in the middle of winter. Your company has fitted the vehicle with IoT sensors that continually monitor wheel slip, air temperature, speed and RPMs. Suddenly, the wheel slip measurement spikes as the air temperature falls below freezing. If the truck or driver can react in milliseconds, an accident can be prevented. If not, the sensor data is meaningless. Event stream processing. Event stream processing systems enable you to act on this information in a timely fashion through real-time data cleansing and analytics.

Spotlight

Data science brings a huge promise to IT security and accordingly to the sprouting of DS teams across all enterprises, and numerous vendors. Indeed DS has the potential to transform the way security is done—yet, the secret sauce is how to do it in a way that actually provides clear value.


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