System/Integrations/Integration

Google BigQuery

Data warehouse

A number that only lives in a warehouse cannot inform a conversation happening on a call right now. Revenue Labs reads the tables a company builds in BigQuery from product, billing and revenue data, and joins them to the right account, so a rep works from one set of numbers.

Connect your stack ↗

Website

https://cloud.google.com/bigquery

From source record to operating state

01 | The tool on its own

Warehoused tables for product, revenue, and usage data.

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02 | With AI bolted on

Gemini helps find and explain data.

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03 | A system that learns

Warehouse data becomes account state.

The tool alone > AI bolted on > AI-native

What changes when Google BigQuery feeds a system that learns

Three jobs Google BigQuery already does, and what each becomes when its evidence joins live company, contact and deal state.

01 | The tool on its own

02 | With AI bolted on

03 | AI-native

Datasets and tables

Warehoused tables for product, revenue, and usage data.

BigQuery stores the tables a company builds from product and revenue data. A data owner still defines schemas, permissions, and joins.

Gemini helps find and explain data.

Gemini works from the datasets and schema it can access. Its answer stays in BigQuery and does not update the live account view.

Warehouse data becomes account state.

Relevant tables are associated with their company, contact, and deal without replacing the warehouse.

SQL queries

SQL turns large tables into a usable answer.

BigQuery lets teams query large datasets with SQL. An analyst still runs the query, checks the result, and decides whether it belongs in a commercial decision.

Gemini generates and explains SQL.

Query drafts remain a draft until an analyst checks and runs them. The draft does not carry the result into every capability or learn from the deal outcome.

A query result reaches the deal.

Usage change, revenue fact, or product event sits beside calls and stages where the next capability can use it.

Data canvas and analysis

Analysis can be queried, charted, and shared.

BigQuery data canvas helps teams find, query, and visualise data. An analyst still selects the tables and reviews the result.

Gemini creates charts and summaries.

Charts and summaries explain selected BigQuery data. They provide no company or deal join, and no test against renewal, expansion, or loss outcomes.

Warehouse signals follow outcomes.

Closed outcomes reveal which warehouse patterns preceded them. The system learns the useful pattern and supplies it to the next account decision.

Runs on it

Capabilities that act on connected evidence

BUILT FOR SECURITY, CONTROL AND SCALE

Connect data securely, capture every agent's activity, and enforce permissions with ease.

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CERTIFIED + COMPLIANT WITH:

ISO 27001:2022

GDPR

CCPA

Data Protection Act 2018

The GTM teams that learn fastest will win.

Connect your stack to a system that learns.

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