The three biggest challenges in preparing IoT data: Getting past the complexity barriers
Sean Kandel | February 01, 2019
The Internet of Things (IoT) is already entrenched in our everyday lives - from wearables and smart watches through to connected TVs and smart home appliances. Businesses, too, are utilising the technology; in a B2B context, connected devices refer to machines and sensors that are used to track everything from machine performance to maintenance requirements. For instance, sensor devices might be found on a production line to track the readiness of the machines and automate predictive maintenance. Or, a hospital might use IoT devices for remote patient monitoring, robotic surgery or dispensing medication. All of these growing sensors, devices, and other connected “things” ultimately mean more data. And lots of it. But with more data come more complex challenges in preparing it. To harness the value of IoT and big data—and deliver innovation-driving insights— industrial organisations must quickly prepare all of this disparate, unstructured data. Below, we’ve named some of the top three challenges in preparing IoT data to leverage it for analysis.