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Issue with data classification in a report of incidents within SLA vs out of SLA


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  While I was creating a repot about the incidents within SLA versus out of SLA, I found out that there is an unclassified data point which I don’t know where it is coming from. Could it be a bug? How to identify the source and eliminate it so that it doesn’t mess up my report? The data point in question is in light blue below

 

The screenshot below shows the metric, time dimension and group by filter for better understanding

 

 

Best answer by eeha0120

Hi again.

I’ve just checked on my instance and yes, those are the Unresolved tickets (which do not have then a Resolution Status).

If you need to omit those, you would need to use an additional filter to include status Resolved/Closed only:

 

Regards,

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5 replies

eeha0120
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  • August 1, 2024

Hi.

I guess it would refer to the tickets that are still not resolved, but I’m not sure.

On the widgets, you can click on the Underlying Data button and check the data: 

It will show you the data which you can filter, adjust columns and export as CSV.

 

Hope this helps.

 

 

Regards,


eeha0120
Skilled Expert
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  • Skilled Expert
  • 738 replies
  • Answer
  • August 1, 2024

Hi again.

I’ve just checked on my instance and yes, those are the Unresolved tickets (which do not have then a Resolution Status).

If you need to omit those, you would need to use an additional filter to include status Resolved/Closed only:

 

Regards,


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  • August 1, 2024

@eeha0120 Thank you!


B9Game
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  • Community Debut
  • 1 reply
  • November 26, 2024

When dealing with data classification in a report that categorizes incidents as within SLA (Service Level Agreement) vs. out of SLA Click, several common issues can arise.


Yasir5588
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  • Community Debut
  • 2 replies
  • January 8, 2025

It seems like there may be confusion or inconsistency in how incidents are being classified within SLA versus outside of SLA. Ensure that the SLA metrics and timeframes are clearly defined, and that incidents are accurately tracked based on the time they were logged and resolved. It's also helpful to implement automated systems or checks to avoid human error in classification.


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