Batch ticket creation?

Hi sleepykat , 

Absolutely, It's possible to create multiple tickets via CSV file!

Here's how you can achieve this using the CSV import option: Navigate to Service Desk > Incidents > Actions > Import here you can import your CSV file and from this link you will get CSV template which can be used to fill out all your tickets details like title, requester, category and all.

Once import is done your tickets will be created.

CC,

Nice info from you. 

Do I need to fill in each column, or wil "Created At" automatically fill in today's date?

Yes, that's right! The "Created At" field will automatically be filled with the date and time the import is done. You only need to fill in the mandatory fields, which are "Title" and "Requester". You can leave other fields empty for now.

OK, just tried a test. 
Got

"Warning! CSV contains invalid dates on row 1, column: 'Created At', date: '', we set the time and date to the time the import was performed. The legal format is 'dd/mm/yyyy' and not 'mm/dd/yyyy'."

I left the cell blank in my CSV.
At the Column Mapping page, I get this:  

So what are they saying in that error msg?

Chazzy… any idea why I’m getting that error?

sleepykat you are probably getting that message because the field is empty and if you are telling the system that there should be something there, by the mappings in the screenshot. This is the platform letting you know that it set the time and date to the current one because there either wasn't a value in that field or the date format wasn't correct. If you don't need to map into that field, meaning you just want the current time, then you can exclude that mapping in the import. 

Hope this helps!

I’ll try it… 

You mean delete that column altogether?

Yup, that will work! If you dont want to set the creation date to something in the past, you can just delete that whole column in your csv or just map it to Nothing in the field mapping. 

Yup, that will work! If you dont want to set the creation date to something in the past, you can just delete that whole column in your csv or just map it to Nothing in the field mapping.