Navy Blue Energy.

Having insight is knowing something has or will happen-for example, knowing that a machine is about to break, possessing information about a problem, or knowing how to resolve a problem by scheduling a repair. The insight will be a part of solving a facility problem. After careful thought on what the insight is saying, an action plan can be put in place.

Data science, and particularly analytics, is used to systematically extract insights from data. For example, the occurrence of rare, random-looking patterns in data streams are early warning signs of a failure.

Data processing that happens at the location where data is created is key. Local insights are used to obtain rapid local action, and data need not be transported. For example, a building can be monitored by scheduling occasional reports (for example, once a minute), rather than continuously sending data to the cloud or a data center. Writing simple applications in an edge compute system is easier, since the resources can be dedicated to that task alone. Also, getting a solution production-ready is also easier, as fewer moving parts exist.

You don't need a degree. However, you must be able to imagine what can be done with existing data (numbers) and new data derived from IoT measurements. For example, if a manufacturing process fails, adding extra measurement points will help detect where the failures originate. Conducting extra measurements and making data comparisons throughout a process provides insight..