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I have a list of users that are connecting to TeamViewer. We have a limited number of lisences that is based on how many users are active at any given time. I have the log on and log off times for all users. I need to create a bar or line graph showing users over time as to how many are logged on at any given time. Any ideas of how to create a visual like this? The count would only change as a user is added or drops off, it wouldn't nessisarily change because the date/time changed. Example: @ 6pm tuesday there were 10 active users, then at 8pm there were 9 then wednesday at 10am there were 11, etc. I hope that makes sense.
What's your sampling rate? Do you need this by hour? by minute?
Please provide sample data (with sensitive information removed) that covers your issue or question completely, in a usable format (not as a screenshot). Leave out anything not related to the issue.
https://community.fabric.microsoft.com/t5/Community-Blog/How-to-provide-sample-data-in-the-Power-BI-...
Please show the expected outcome based on the sample data you provided.
https://community.fabric.microsoft.com/t5/Desktop/How-to-Get-Your-Question-Answered-Quickly/m-p/1447...
861329830 | 2/6/2023 9:44 | 2/13/2023 20:05 |
1531804798 | 2/6/2023 9:44 | 2/13/2023 20:05 |
1531804798 | 3/1/2023 7:12 | 3/8/2023 10:24 |
861329830 | 3/1/2023 7:11 | 3/8/2023 10:24 |
1531804798 | 2/22/2023 14:12 | 3/1/2023 7:12 |
861329830 | 2/17/2023 8:56 | 2/22/2023 14:12 |
861329830 | 3/8/2023 10:27 | 3/13/2023 10:23 |
1531804798 | 3/8/2023 10:27 | 3/13/2023 10:23 |
861329830 | 2/22/2023 14:12 | 2/27/2023 1:37 |
1531804798 | 2/17/2023 8:55 | 2/21/2023 19:55 |
1531804798 | 1/23/2023 7:19 | 1/27/2023 10:07 |
861329830 | 2/2/2023 7:40 | 2/6/2023 9:43 |
1531804798 | 2/2/2023 7:40 | 2/6/2023 9:43 |
1053809758 | 5/22/2023 8:30 | 5/25/2023 12:26 |
861936026 | 5/23/2023 14:08 | 5/26/2023 17:02 |
861329830 | 3/17/2023 7:33 | 3/20/2023 9:20 |
1531804798 | 3/17/2023 7:34 | 3/20/2023 9:07 |
861329830 | 5/12/2023 9:21 | 5/15/2023 8:00 |
1030018397 | 8/8/2023 9:33 | 8/11/2023 6:43 |
1531804798 | 7/14/2023 11:13 | 7/17/2023 8:02 |
1642777017 | 7/14/2023 11:17 | 7/17/2023 7:53 |
1897949114 | 8/4/2023 15:51 | 8/7/2023 8:55 |
1442553765 | 6/16/2023 13:11 | 6/18/2023 23:18 |
1053809758 | 5/15/2023 11:49 | 5/17/2023 13:59 |
1159315116 | 8/16/2023 15:19 | 8/18/2023 16:02 |
615316499 | 5/18/2023 20:48 | 5/20/2023 14:05 |
615316499 | 3/13/2023 1:59 | 3/14/2023 19:08 |
950952136 | 6/9/2023 14:15 | 6/11/2023 6:42 |
1413405182 | 6/16/2023 16:55 | 6/18/2023 5:14 |
1531804798 | 2/15/2023 7:10 | 2/16/2023 18:03 |
1053809758 | 8/3/2023 8:02 | 8/4/2023 16:59 |
1642777017 | 6/1/2023 7:45 | 6/2/2023 14:30 |
861329830 | 3/15/2023 7:15 | 3/16/2023 13:28 |
1531804798 | 3/15/2023 7:16 | 3/16/2023 13:28 |
1375652509 | 8/24/2023 8:32 | 8/25/2023 13:32 |
567428825 | 2/17/2023 7:51 | 2/18/2023 12:27 |
1436744071 | 1/30/2023 10:43 | 1/31/2023 14:34 |
1896524992 | 5/31/2023 11:45 | 6/1/2023 15:21 |
1053809758 | 6/1/2023 8:41 | 6/2/2023 10:58 |
so "max unique users in the selected timeframe" ?
Yeah, maybe max number of users logged on at any given time for each day....
Or maybe I can interest you in a chart based solution?
That might work, as long as i can get the max total out of it.
Nah, not really.
Please show your Dates table. Does it need hourly granularity?
I thought i did below. I added as a table, but it doesn't look formatted well. I was thinking the max by day.
Really appreciate your help/time on this one... I'm not sure exactly... I might need a bit of guidence on how I can/should display this. In my head, I think maybe the max user count per day/week (at a given time) might be most appropriate. Basically we have a limited number of licenses for an app. We can see who is logged on and when. We need to see how close we are to going over our alloted users at any given time (max 10). We will required new group licenses if we go over our limit. Here are examples of the data received:
ID | Session type | Start | End |
1053809758 | Remote Control | 5/22/2023 8:30 | 5/25/2023 12:26 |
861936026 | Remote Control | 5/23/2023 14:08 | 5/26/2023 17:02 |
861329830 | Remote Control | 3/17/2023 7:33 | 3/20/2023 9:20 |
1531804798 | Remote Control | 3/17/2023 7:34 | 3/20/2023 9:07 |
861329830 | Remote Control | 5/12/2023 9:21 | 5/15/2023 8:00 |
1030018397 | Remote Control | 8/8/2023 9:33 | 8/11/2023 6:43 |
1531804798 | Remote Control | 7/14/2023 11:13 | 7/17/2023 8:02 |
1642777017 | Remote Control | 7/14/2023 11:17 | 7/17/2023 7:53 |
1897949114 | Remote Control | 8/4/2023 15:51 | 8/7/2023 8:55 |
1442553765 | Remote Control | 6/16/2023 13:11 | 6/18/2023 23:18 |
1053809758 | Remote Control | 5/15/2023 11:49 | 5/17/2023 13:59 |
1159315116 | Remote Control | 8/16/2023 15:19 | 8/18/2023 16:02 |
615316499 | Remote Control | 5/18/2023 20:48 | 5/20/2023 14:05 |
615316499 | Remote Control | 3/13/2023 1:59 | 3/14/2023 19:08 |
950952136 | Remote Control | 6/9/2023 14:15 | 6/11/2023 6:42 |
1413405182 | Remote Control | 6/16/2023 16:55 | 6/18/2023 5:14 |
1531804798 | Remote Control | 2/15/2023 7:10 | 2/16/2023 18:03 |
1053809758 | Remote Control | 8/3/2023 8:02 | 8/4/2023 16:59 |
1642777017 | Remote Control | 6/1/2023 7:45 | 6/2/2023 14:30 |
861329830 | Remote Control | 3/15/2023 7:15 | 3/16/2023 13:28 |
1531804798 | Remote Control | 3/15/2023 7:16 | 3/16/2023 13:28 |
User | Count |
---|---|
22 | |
11 | |
8 | |
6 | |
6 |
User | Count |
---|---|
26 | |
13 | |
11 | |
9 | |
6 |