October might be a spooky month, but we’re doing our best to make incidents less scary. We released a number of updates this month that focus on two main areas: Let’s jump in.
Industrial IoT (IIoT) machines and sensors generate valuable time series data. It’s impossible to derive the insights necessary to inform decisions as a company to produce or operate more efficiently without sending operational technology (OT) data to informational technology (IT) systems.
The shift in remote working has seen an increase in demand to utilize smartphones to host meetings, check emails and message colleagues on Microsoft Teams. Keeping up with this trend, the Kelverion team have created a mobile app version of our popular Self-Service Automation Portal, which previously has been a web-based solution typically used on a desktop device. The portal is available for iPhone devices and can be downloaded from iOS app store.
SharePoint Online (SPO) has become a cornerstone for many organizations seeking a robust, scalable, and collaborative platform. It’s a place where teams can seamlessly work together, share documents, and enhance their workflow efficiency. However, while SPO offers a plethora of benefits, the cost associated with its usage can be a potential hurdle, especially for businesses with large volumes of data.
Welcome to the second chapter of the handbook on Anomaly Detection for Time Series Data! This series of blog posts aims to provide an in-depth look into the fundamentals of anomaly detection and root cause analysis. It will also address the challenges posed by the time-series characteristics of the data and demystify technical jargon by breaking it down into easily understandable language. This blog post (Chapter 2) is focused on different types of anomalies.
If there’s anything I’ve learned, monitoring data is the lifeblood of the business and a superpower for any IT practitioner. Monitoring allows organizations to react to changes, identify and recover, and understand the true health of the business.
