BigQuery Consulting on Google Cloud

BigQuery for marketing and sales data

BigQuery is Google Cloud's data warehouse: a serverless analytics database built to query large volumes of data with SQL. For marketing teams it has a clear advantage: GA4 exports its events to BigQuery natively, and Google Ads data loads through the BigQuery Data Transfer Service. The two sources marketing relies on most arrive without custom code.

The hard part comes next. The GA4 export creates one table per day with event parameters nested inside each row, and anyone querying it for the first time finds that a simple question, like how many sessions came from a campaign, takes a fair amount of SQL. On top of that, BigQuery bills for the data each query processes (or for reserved capacity), so a poorly written query behind a dashboard runs again every time someone opens it.

Our job as your BigQuery consultant is to make it the single source of truth for sales and marketing, with data already modeled so nobody has to wrestle with raw event tables.

What our BigQuery consulting covers

GA4 and Google Ads in BigQuery

We set up the GA4 export and the Google Ads transfer, then turn raw events into tables people understand: sessions, conversions, campaigns, spend.

CRM, ERP and other sources

HubSpot, Salesforce, your ERP, Meta Ads or your e-commerce platform land in the same project, so campaigns can be matched to real opportunities and revenue.

Modeling with dbt

Version-controlled, tested transformations in layers, with business definitions written down: what a qualified lead is, what counts as a sale, which campaign gets the credit.

Query costs under control

Date-partitioned tables, clustering on the fields people filter by most, summary tables for dashboards and maximum-bytes-billed limits so no single query gets out of hand.

Access and data location

Dataset-level permissions and, where needed, row-level access policies. Data stays in the Google Cloud region you choose, such as the EU multi-region.

Models with Vertex AI

On the same data we train predictive models, such as customer churn risk. Simple ones can be built with BigQuery ML in SQL; for the rest we use Vertex AI.

How we keep BigQuery costs predictable

Under on-demand pricing, BigQuery charges for the data each query reads, not for how long it runs. So cost depends more on how tables are built than on how many people use them. In general, we:

Partition large tables by date, so a last-month query doesn't scan the full history.
Read only the columns needed: selecting every column is billed in full even if you limit the rows returned.
Build summary tables for dashboards instead of letting Looker Studio or Power BI hit raw events.
Set per-query limits and per-user quotas, and regularly review which queries cost the most.
Check against real usage whether on-demand pricing or reserved capacity suits you better.

BigQuery, Sales Copilot and AI for sales

BigQuery is not only for dashboards. Our Sales Copilot, the AI agent that answers questions like “How is my pipeline tracking against target?” in plain language, runs on BigQuery and your data warehouse. It reads the same source as your reports, with no data replication and no new silos, inside your own Google Cloud environment. Your data never leaves it and is never used to train models.

So when we build a Google Cloud data warehouse, we design it for both: the dashboards you need today and a sales team that can simply ask tomorrow.

BigQuery consulting FAQ

How much does BigQuery cost?

It depends mainly on how much data your queries read and how your tables are built. Before building anything, we explain which Google Cloud pricing model fits and how we will monitor spend.

Why export GA4 to BigQuery if I already have GA4 reports?

Because BigQuery holds the raw, unaggregated events, which you can join with CRM and revenue data, something the GA4 interface can't do. And the history stays in your own project.

Does my team need to know SQL?

To maintain the model, yes. To use it, no: your team works with dashboards in Looker Studio, Looker or Power BI, or asks questions in plain language through Sales Copilot.

Is BigQuery GDPR compliant?

BigQuery lets you choose where data is stored, control who accesses it and log that access. Compliance depends on how it is set up, and we design for it from the start.

Sales Copilot Looker Studio dashboards Data strategy

Let's talk about your Google Cloud data warehouse

A 30-minute call to look at your sources and what you want from them. We'll tell you if we can help, and if we can't, we'll tell you that too.

Book a 30-minute call