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Time to read: 8 minutes  Posted by John Harrington How much time do you spend cleaning data?
If your factory is like most connected operations, you probably have tons of raw data streaming from connected devices to existing enterprise systems, bespoke databases, and a cloud data lake. This architecture often leads to inconsistent or even unusable data for several reasons. We know the Cloud is a key tool for digital transformation. It provides the scalability and storage capacity you need to collect and interpret vast amounts of data coming from the operations level. However, by nature, cloud platforms are IT-focused tools. They structure data differently than operational systems, which means IT must spend a lot of time cleaning the data before it can be used. And if the data moves directly to different enterprise systems, multiple teams across the organization will clean the data independently, leading to different versions of the truth.
Time to read: 6 minutes
 Posted by Aron Semle
Let’s talk about getting OPC data into Microsoft Azure. When you search this phrase in Google, 90% of results provide this use case: streaming sensor data to the Cloud.
If your Industry 4.0 solution is streaming sensor data to the Cloud, you're doing it wrong. Now let me explain. On the factory floor, we have machines driven by PLCs, and we typically have an OPC server connected to those PLCs that feeds data into an HMI. OPC servers and HMIs work with tags, which are discrete streams of data. For example, one tag might be for pressure and another might represent the on and off state of the machine. When cloud technology like Microsoft Azure first entered the scene, vendors created IoT gateways to connect to the OPC server and send tag streams to the Cloud in a JSON format. It was the easiest thing to do, and once that connection was made, we thought we were done. |
