Extract Data Connector for Google Data Studio to Speed Up Your Reports
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- Опубліковано 23 лип 2024
- Is your Google Data Studio Report loading slowly? It could be due to the volume and nature of the data requests you are making to your external Data Source, like Google Analytics.
It’s for that reason that you might want to consider using something called the Extract Data Connector. It preloads your data for a fast reporting user experience.
OUTLINE:
00:00 - Intro
01:32 - How live data is pulled in
02:19 - An example of a slow report
02:58 - Setting up the “Extract Data” Connector
06:25 - The “Auto-Update” setting
08:42 - Adding “Extract Data” as a Data Source
12:24 - The limitations of using Extracted Data
13:50 - Summary
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What’s the longest you’ve had to wait for a chart to load? 😂
The same report sometimes takes 10 minutes and other times more than 30 minutes. This was definitely helpful, thank you for the video!
forever...
still waiting..
great video, thanks! Very helpful.
Thank you again!
Thank you, once you have created the data extract and automated refresh - is there any way to automate a collection of the data via CSV rather than on the dashboard?
this is amazing!
Great video!
Amazing! Thxs!
Great video! Is 'Auto-Update' in 'Extract Data' the same thing as 'Data Freshness' when creating a standard GA data connection in GDS?
I am trying to connect the Looker report to G4 data using the "extract data" connector. For some reason, I can't see an account I am looking to connect but I see other accounts. Just to add I am the admin on all. Why I cant see them ?
Can we blend the extracted data?
Is it possible to blend Extracted Data Sources ?
Sorry, we encountered an error and were unable to complete your request. Error ID: 08d94c1e Anyone know the fix for this?
Thanks for the video! I was wondering, why is there a significative difference between the users in each chart?
Interesting observation. I'll try my best to explain:
Users is a unique metric in Google Analytics because the sum of users within a date range is not equal to the sum of user per each day within that date range. That's because a user can visit your website on multiple days through the date range.
For example, if your website has only two users, I and Julian, and we visit your website every day over one month, the number of total users you've had in that month equals to 2 , and if look at each day individually, you'll see that you've had 2 users per day as well. The sum of users isn't 30x2=60, it's 2.
When you connect directly to GA, each row will receive the number of users for that day only, and the total row will receive the deduplicated total number of users. So if someone visits your website 10 times in that date range, they will show up on each row, but they'll be counted only once in the total row. That's because GA "knows" those 10 visits were actually from the same user.
Now, when you extract data, you're breaking the direct link to the GA and instead of storing a list of numbers in a table in Data Studio, now when Data Studio wants to show the total, it will sum all the daily number of users, because it has no idea what this metric is, and that some users might have visited the website more than once. That's why the number of users in an extracted data source is always more than that of the live connection to GA.
Other metrics, like sessions, transactions, page views, revenue, etc. are not affected by this issue.
Extracted data could be really misleading for users and new users.
@@siavashkanani Thank you so much for your detailed response! Didn't thought about this. I'll take this in consideration when I use this.
@@siavashkanani very nice explanation thanks
unfortunately the extract shows different values (even in your video Users at 12:40) @MeasureSchool do you know any solution for this?
@nokillnina @jfb4106 I have same problems, Total Users metrics is heavily inflated
@@jabihmobil unfortunately I still don'T have any solution
8-18-2023 same error here
If you use segments it will probably show a lot of difference in the load time.
Does this mean that data won't be sampling data anymore if we use the Data Extractor?
The data will still be sampled at the time of extraction.
Hello Ahmad, thanks for the great instruction. After a lot of trial and error ("Failed to extract data into looker studio"), I finally got there with some GA4 data. Now, I face another issue - most of the measures are heavily inflated. I played around with basic settings for numbers using Sum or none aggregation method but it does not change the picture. Does someone has any experience to cope with that?
Also didn't find solution to this "problem" yet. It's not a bug, but a behavior because of the extraction. See explanation about unique users below.
@@DEKRADigitalMarketing Thank you! Yes, I know about the unique users problem but as far as I´m concerned this is true also for current GA UA. And it does not explain why also other measures flow in waves around truth. My best guess is, it is because I try to pull too many measures/dimensions at once. The challenge is if you split it, there are very limited options to join results back into one table ...
@JB Yes, I have now tried to split the extraction into different sources. But I'm still not satisfied with the result and a lot of maintenance + error sources...
@@DEKRADigitalMarketing Agreed - I also tried this and with each variation I get a different result for the same measure - which is crazy.
@@jfb4106 It helped me to recreate the metrics/dimensions in an explorer report directly in GA4 and compared the numbers with looker studio results. Would love to work just with the explorer reports in GA4, but they are read-only and not really shareable... It's just a big mess with this quota limits :D