BigQuery
& Big Data Warehouse

GA4's interface applies sampling to large or complex queries, limits how far back you can look, and can only slice your data along the dimensions Google exposes. The BigQuery export gives you every raw event with no sampling, retained for as long as you choose, queryable any way you like. If you've ever hit a question GA4's reports couldn't answer, that's the gap BigQuery fills.

For most mid-sized sites the cost is modest — you pay Google Cloud for storage and for the data each query scans, and the free tier absorbs a meaningful share of it. High-traffic properties cost more, which is why we design the schema and the query patterns to keep scanning efficient rather than letting costs grow unchecked.

A complete setup covers configuring and validating the GA4 to BigQuery export, documenting the schema, building the queries and data models your reporting depends on, connecting the warehouse to Looker Studio or your other downstream tools, and monitoring the pipeline so breaks are caught before they reach your reports.

The GA4 export only starts collecting from the day it's enabled — it is not backfilled, which is the single best reason to turn it on now even if you're not ready to use it yet. Where historical data exists in other systems, we can load it separately to give your models a longer baseline.

No. We build the queries and models, then connect them to Looker Studio so your team consumes the output through dashboards rather than writing SQL. If you do have analysts, they get a documented, well-structured warehouse to work in rather than raw tables and guesswork.