Real ChatGPT answer · index seedkxVzHpYc7nMcompleteB2B software · data and analytics platformsinformational
I keep getting messy JSON payloads from our Google Analytics 4 export pipeline into BigQuery, so what is the current recommended method to flatten these user event arrays for monthly reporting?
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I keep getting messy JSON payloads from our Google Analytics 4 export pipeline into BigQuery, so what is the current recommended method to flatten these user event arrays for monthly reporting?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
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Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
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Google Analytics 4 BigQuery export flatten event_params arrays UNNEST recommended monthly reporting official documentation Google ↗
GA4 BigQuery export schema repeated fields event_params items UNNEST official docs Google ↗
- BigQuery Export schema · support.google.com
- BigQuery export schemas | Google Analytics | Google for Developers · developers.google.com
- Basic queries for Google Analytics event data export | Google for Developers · developers.google.com
- Specify nested and repeated columns in table schemas | BigQuery | Google Cloud Documentation · docs.cloud.google.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Google Analytics 4 BigQuery export flatten event_params arrays UNNEST recommended monthly reporting official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 | |
GA4 BigQuery export schema repeated fields event_params items UNNEST official docs OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |