Abstract: Various embodiments described herein relate to predicting potential incident event structures based on multi-model analysis. In this regard, a potential incident event with respect to aggregated data associated with one or more data sources is identified. In response to the potential incident event, one or more potential incident event data structures are identified based at least in part on the aggregated data. Additionally, in response to the potential incident event, one or more actions are performed based at least in part on the one or more potential incident event data structures.

Abstract: Various embodiments described herein relate to a contextualized time series database and/or multi-tenant server system deployment. In this regard, a request to obtain one or more insights with respect to contextualized time series data related to one or more assets is received. The request includes at least an insight descriptor describing a goal for the one or more insights. In response to the request, attributes of the contextualized time series data are correlated based on the insight descriptor to provide the one or more insights. Furthermore, in response to the request, one or more actions related to the one or more assets are performed based on the one or more insights.

Abstract: Various embodiments described herein relate to predicting potential incident event structures based on multi-model analysis. In this regard, a potential incident event with respect to aggregated data associated with one or more data sources is identified. In response to the potential incident event, one or more potential incident event data structures are identified based at least in part on the aggregated data. Additionally, in response to the potential incident event, one or more actions are performed based at least in part on the one or more potential incident event data structures.