In this ESG Video Blog, ESG's Eugene Signorini discusses how, when thinking about IoT application design, we really ought to be thinking about the IoT data journey.
Hi. I'm Gene Signorini, Senior Analyst at ESG. I recently discussed the confusion surrounding the IoT platform space. It seems to me that we, and by "we" I mean the broader market participants and vendors in the IoT ecosystem, spend an awful lot of time talking about technology, when in reality we should be speaking about data, and more specifically, the data journey.
I spent a lot of time in my analyst and consulting career examining mobile applications. And one of the key principles around application design that has emerged over the last several years is the concept of user experience. And really, what that means is understanding the user journey and then applying technology where appropriate on that journey. But when it comes to IoT applications, we're most often talking about machines, and equipment and sensors, and not users per se. And the reality is that the most important element of an IoT solution is the data. Data is the lifeblood of IoT, since data captured from sensors can be transformed into information that can impact business processes and connected products. So when thinking about IoT application design, we really ought to be thinking about an IoT data journey. We need to think about the path that IoT data take from the sensor all the way through to applications and potentially back again.
For example, if we start at the device or sensor itself, we can think about what data we need to capture and how we need to capture it. How will the device need to be connected to facilitate this? What type of security is required for our sensor data? Is there processing we need to do at the device or the sensor itself?
The next step of the path we can think about has to happen at the edge. Do we need to collect data from multiple devices and sensors, aggregate the data, convert and pass the data for transmission to a central source in the cloud or data center? Do we need to conduct some degree of analytics onsite for critical operations? From there, data will travel to the cloud or a data center for further processing and more advanced analytics, which might include integration with other data sources. These analytics can be used to adjust business rules and actuate processes back at the edge or device. We can also think about data storage and long-term data management.
Finally, we need to think about how the data will ultimately be consumed and applied. Often, this means that there's a user, a human involved. We may need to provide the data to business analyst or data scientist for use in business process analysis. Perhaps the data is exposed to operations managers or executives in the form of dashboards, or we may want to provide sensor and machine data to technicians and engineers via mobile applications.
If we think about data the same way we consider our user's needs when designing applications, we can begin to understand solution requirements first and then apply the appropriate technology for the IoT solution. The benefit of thinking about IoT as a data journey is that it helps inform how solutions need to be designed to achieve the overall business objective.