In our industrial Internet of Things (IIoT) data problem series, we’ve arrived at the tricky issue of misidentified data in remote monitoring systems. Misidentified data is high-quality, complete, and on time. However, the identity of the asset it represents in the remote monitoring system has been mislabeled. As a result, the misidentified data is highly … Read more
Through our data problem series, we’ve covered several data challenges that industrial companies face when pursuing digital projects. Some struggle with low-quality data, while others are limited by data silos and legacy systems. Many of the specific issues we’ve covered are symptoms of the Digital Age. We have more data than ever before at our … Read more
Bad data collected by a remote monitoring system can wreak havoc on industrial organizations. When prevalent in business processes and analysis, bad data creates a fundamental disconnect between what is actually happening in the field and what decision-makers think is happening in the field. Put simply, bad data misrepresents reality. It “lies” about the current … Read more