When it comes to Big Data, we often think of user (human) generated social media data. But sensor (machine) generated data is a much bigger story as sensor data will drive the next wave of productivity growth and innovation. Consider this for example, “Boeing jet engines can produce 10 terabytes of operational information for every 30 minutes they turn.
When it comes to Big Data, we often think of user (human) generated social media data. But sensor (machine) generated data is a much bigger story as sensor data will drive the next wave of productivity growth and innovation. Consider this for example, “Boeing jet engines can produce 10 terabytes of operational information for every 30 minutes they turn. A four engine jumbo jet can create 640 terabytes of data on just one Atlantic crossing, multiply that by the more than 25,000 flights flown each day” (Source: Information Management). Almost all of this data is lost on completion of the flight, but this is about to change.
Thanks to Big Data tools and technology, we can identify, store, retrieve and analyze this data in a cost effective and timely manner. Think about the possibilities this opens up in the area of preventive maintenance and fault prevention – resulting in reduced flight delays and cancellations because of technical issues with the plane. And given the cost effectiveness of Big Data tools and technology, vast amount of sensor data can be analyzed in almost real time in a wide array of fields, not just in aircraft maintenance.
Smart electric meters are another good example of sensors generating vast amount of data that can be used to drive productivity. Because of smart meters, electricity providers can read the meter once every 15 minutes rather than once a month. This not only eliminates the need to send some one for meter reading, but as the meter is read once every fifteen minutes, electricity can be priced differently for peak and off-peak hours. Pricing can be used to shape the demand curve during peak hours, eliminating the need for creating additional generating capacity just to meet peak demand, saving electricity providers millions of dollars worth of investment in generating capacity and plant maintenance costs.
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These are just two examples. Now imagine the possibilities of what can done with a vast array of sensor data that is analyzed and used in industrial/business processes in real-time. In my opinion, we are on the cusp of a major sensor data driven productivity revolution that will fundamentally change the way we do business, for the better!
