Forum Discussion
Google analytics to Power BI - counters mismatch with adding new metrics and dimensions
I am working on GA reporting metrics in Power BI via reporting API.
While I create a query with some very basic attributes like sessions and users, I get same values as I can see directly in google analytics dashboard. but when I add more dimensions and attributes, say, user type, pageviews or gender etc, alingwith users and sessions, the value of users and sessions is inflated.
I have tried to go through various documentations, where I know there are some restrictions that not all dimensions and attributes can be put together, but in this case, GA has allowed me to add these basic attributes togehter but the results are not matching. Is there any documentation to explain this behaviur, or has anyone experienced anything like this. has this to do something to do with binning, though I would expect, even if the difference is due to different binnings on different counters, the difference should be a smaller value, not the ones I am getting, which is huge(multiple times of error ) not just few percent of error
- Hi there I have had the same issue. And it appears to be because you are using the GA cube that when you put in certain metrics it is cross referencing the data, which causes the numbers to inflate.
What I did was to have different queries where the data matches GA.
It did take me some time to read through the GA definitions to understand what the one value was which was causing the numbers to inflate. As soon as I put those metrics into their own query (table) everything matched back to GA.
13 Replies
- GilbertQ
Super User
Hi there I have had the same issue. And it appears to be because you are using the GA cube that when you put in certain metrics it is cross referencing the data, which causes the numbers to inflate.
What I did was to have different queries where the data matches GA.
It did take me some time to read through the GA definitions to understand what the one value was which was causing the numbers to inflate. As soon as I put those metrics into their own query (table) everything matched back to GA.- Thanks GilbertQ for sharing your similar experience and advice. Yes, I am trying to do same, though it involves lot of hit n trial.
The GA documentation is not very helpful in this regard.Hey, i am trying to do the same thing and am not getting the correct value for Users.
I have tried to pull the User data alone with only a date range. The number is closer to what it should be, but still isnt correct what else can i do to get the correct User value?
v-ljerr-msftMicrosoft Employee
Hi Anonymous,
Have you tried the solution provided by GilbertQ above? Does it work in your scenario? If it works, could you accept it as solution to close this thread?
If you still have any question on this issue, feel free to post here. :smileyhappy:
Regards
It will help to have different queries where the data matches GA. When you separate queries in their own query, table problems should disappear.
There is a software company Windsor.ai that has solved problems integrating Google Analytics and Power BI, you can check out some of their solutions and proposals on how to set up this integration here https://www.windsor.ai/google-analytics-raw-google-ads-facebook-and-windsor-ai-data-into-microsoft-powerbi/
This issue still exists for me - the 'user' data that shows in BIU doesn't match GA, whatever you do.
In the end, I created the report in Google Data Studio (FOC, and has a built-in connecter to GA), them embedded the Google Data Studio report in a Power BI dashboard widget. Far from ideal, but it works and at least the data is correct.
ReportMasterPost Partisan
Hi. As a workaround, maybe you can try to test your connection with a 3rd party connector. I've tried windsor.ai, supemetrics and funnel.io. I stayed with windsor because it is much cheaper so just to let you know other options. In case you wonder, to make the connection first search for the GA connector in the data sources list:
After that, just grant access to your GA account using your credentials, then on preview and destination page you will see a preview of your GA fields:
There just select the fields you need. Finally, just select PBI as your data destination and finally just copy and paste the url on PBI --> Get Data --> Web --> Paste the url.
