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The discrepancy you’re experiencing between the Looker report and your Google BigQuery results could be due to a number of reasons. A likely factor could be how the ‘views’ are defined in each platform (Looker vs Google BigQuery). There may be differing criteria for defining a ‘view’, thus contributing to a difference in counts. For instance, unique views could be counted in one platform while total views, including multiple views by the same visitors, could be counted in the other. Also, there could be a mismatch in the date filtering between the platforms or the data may not have been updated synchronously on both platforms, causing an apparent discrepancy. It could also be a result of Looker using a different query or join-condition to compute the total views. It might be helpful to directly compare the Looker query with your BigQuery query to identify potential differences.
Moreover, the data you’re querying with BigQuery could potentially be an unclean dataset, and might require some preprocessing to match the criteria applied in your Looker-Studio report. This could include removing duplicate entries, filtering out irrelevant data, or transforming the data into a suitable format. Finally, it could be a simple error in your BigQuery syntax leading to incorrect results being returned. A thorough review of the code and comparison with Looker’s query could help identify and fix the issue.
