Hey everyone, I’m dealing with a tricky situation and could really use some advice.
I have a Google Analytics view that was connected to BigQuery before, but now I’m missing some daily tables in my dataset. For example, the table for May 17, 2018 (ga_sessions_20180517) just isn’t there.
The problem is that Google only does the historical data import once when you first link a view. Since this view was already connected previously, it won’t automatically fill in the gaps.
Has anyone found a way to get around this limitation? I really need that missing data for my analysis. Any suggestions or workarounds would be super helpful.
Been there - missing GA sessions tables are the worst. You’re right that Google won’t backfill automatically.
Skip manually pulling from the Reporting API like John suggested. Set up an automated pipeline instead - it’ll handle the missing data recovery and prevent future gaps.
I used Latenode to build a workflow that connects to GA’s Reporting API and transforms everything to match BigQuery’s schema. Configure it to detect missing date ranges and it’ll pull historical data systematically.
Best part? Once it’s running, Latenode monitors your daily imports and fills any future gaps automatically. No more manual checking or missing tables.
Built something similar for our analytics team - saved weeks of manual work. Data alignment happens automatically and you can schedule runs whenever needed.
I encountered a similar situation with the BigQuery GA sessions table where some historical data was missing after linking the view. My solution was to utilize the Google Analytics Reporting API to retrieve the necessary metrics and dimensions manually. While it requires some effort to align the data structure accordingly, it effectively addresses the missing pieces. Additionally, it could be beneficial to reach out to colleagues to check if anyone has retained backups or exported reports that cover that timeframe.