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“Dark data” sounds like a concept from cosmology, but it’s actually the term data scientists invoke for information that enterprises generate but don’t use: as much as 90 percent by some estimates. The Internet of Things (IoT) only amplifies the problem and intensifies the need for new ways to manage information. In short, big data is about to get a lot bigger.
In addition, as sensors become cheaper, better, and more versatile, designers are taking full advantage. For example, a new field called social analytics uses information from biometric sensors, video, and social media to gain insights into behavior. In one experiment, researchers created an “agitation index” for sports coaches, which they correlated with game outcomes to identify more successful coaching behaviors. (The research is mum on how many of the coaches adopted the suggested behaviors.)
To prepare for this avalanche, CIOs must rethink how they analyze data. Existing computational paradigms won’t do the trick. Enterprises will turn to high-performance computing for IoT and other data analysis. Cognitive computing—an umbrella term for a range of disciplines in artificial intelligence and signal processing—shows great promise. Combining cognitive capabilities with IoT makes it possible to analyze huge amounts of sensor data and extract insights that improve decision-making. Cognitive computing will also help companies ingest compute-hungry technology advances such as digital twins.
Even with IoT analytics in its infancy, CIOs need to act now. Experiment to understand how specific sensors can generate new insights about product operation and business processes. Brainstorm with product managers about which IoT analyses would have value and why. Take part in industry groups that define IoT standards. Above all, create a vision for IoT analytics that fits your company. Then take charge of making it a reality.
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