Hi Kai - our Augmented Operation aims at doing that Kai, more specifically I'm referring to the Automated Incident Tracking (Automatic incident tracking | DataMiner Docs).

This capability uses a plethora of data points and information to automatically group multiple alarm messages together.  In other words, to bundle all alarms that are highly likely related to each other (i.e. they have a single root cause).  All alarms are grouped in the alarm console, similar to the example below.  If you are looking for the alarm that came in first, then it would be the one at the bottom of that group.

In this case, a failure on the main transmitter site (input of a satellite receiver feeding into that site) seems to be the likely cause of various other alarms, down the slave transmitter sites that are also fed by this main transmitter site.

NOTE: you are right in referring to the first alarm as being the most likely root cause, but that's not necessarily always the case.  There's a very wide range of different types of protocols, interfaces and products out there, and different data collection techniques that are applied across them depending on what is available, and it is not impossible for symptomatic alarms to be reported earlier than the actual root cause alarm.

In any case, Automatic Incident Tracking is a very promising technology that works completely autonomously (i.e. one of the big advantages is that it does not require manual definitions and configuration), and I would like to note a few things about this:

• we are continuously evolving and improving all Augmented Operation capabilities, and they become better, stronger and more accurate with every new release of DataMiner - this is what the future is about, and very much worth looking into for any DataMiner users.
• this kind of capabilities is very unique to DataMiner, as we have that exclusive unified digital twin of the entire operation, and this is really a prerequisite to being able to do something like this - BUT that also means that one has to make sure that they have a clean configuration of DataMiner, or in other words a proper base line set-up (e.g. nicely organize the elements in meaningful views, leverage IDP to properly document locations of physical assets, etc.).  If you create a pile of garbage to begin with when it comes down to your set-up of DataMiner, then obviously you cannot expect very clean results (i.e. also a human without background information would be challenged to draw meaningful conclusions from a pile of garbage).

A lot more to be said about this, but you can also read up on this in the documentation link provided.

Cheers,

Ben