TL;DR BigQuery is Google’s data warehouse — it stores all your data in one place so you can build reports across sources without spreadsheets. You don’t need to be technical to benefit from it. Book a 20-min call to find out if BigQuery is right for your team.
What is BigQuery, in plain English?
BigQuery is a database. A very big, very fast database that lives in the cloud.
Think of it as a giant spreadsheet that can hold billions of rows, never crashes, and connects to everything — your ad platforms, your CRM, your website analytics, your ecommerce data.
Unlike a spreadsheet, it doesn’t slow down when you add more data. It’s designed to handle scale.
Why should non-technical teams care?
You care because BigQuery solves the “data lives in 15 different places” problem.
Right now, your marketing data is in Google Ads. Your website data is in GA4. Your CRM data is in HubSpot. Your sales data is in Shopify. Your finance data is in Xero.
Want a single report that shows how ad spend connects to actual revenue? You need all that data in one place. That place is BigQuery.
What BigQuery is NOT
It’s not a dashboard. You don’t look at BigQuery directly. It’s the engine under the hood. Your dashboards (Looker Studio, Power BI, Tableau) sit on top of it.
It’s not a replacement for your existing tools. You still use GA4, Google Ads, and your CRM. BigQuery just copies and combines the data from all of them.
It’s not something you need to code every day. Once it’s set up, it runs automatically. Your team interacts with the dashboards, not with BigQuery itself.
It’s not expensive. Google gives you 10GB of free storage and 1TB of free queries per month. Most small-to-medium businesses run their entire analytics on less than £50/month.
When your team needs BigQuery
Not every business needs a data warehouse. Here’s when it becomes necessary:
| Situation | Do you need BigQuery? |
|---|---|
| Single marketing channel, simple reporting | No — platform dashboards are fine |
| Multiple channels, need cross-channel view | Yes |
| GA4 data is sampled (high traffic) | Yes — BigQuery export gives unsampled data |
| Blending ad spend with revenue data | Yes |
| Client reporting across 10+ accounts | Yes |
| Historical data beyond platform retention limits | Yes |
| Custom attribution models | Yes |
| Compliance/audit requirements for data | Yes |
The tipping point is usually when you find yourself exporting CSVs from three or more platforms and combining them in Google Sheets. That’s the signal.
How data gets into BigQuery
Data doesn’t magically appear in BigQuery. It needs to be piped in. There are three ways:
Native integrations
Some platforms push data directly to BigQuery. GA4 has a free BigQuery export. Google Ads can connect natively. These are the easiest.
ETL/ELT tools
Tools like Fivetran, Stitch, or Airbyte connect to hundreds of platforms and automatically sync data into BigQuery. They handle authentication, schema changes, and error recovery.
This is what we use at Chartica — Fivetran handles the pipeline so data flows reliably without manual intervention.
Custom scripts
For niche tools or custom APIs, you might need a developer to write a connector. This is the last resort — more maintenance, more fragility.
What happens once data is in BigQuery
Once your data lands in BigQuery, it goes through a process:
1. Raw data lands. Exact copy from the source platform. Messy, granular, not report-ready.
2. Transformation. SQL queries clean, combine, and reshape the data. Ad spend from Google and Meta gets unified into one format. Revenue gets matched to campaigns.
3. Reporting layer. Clean, transformed tables that your dashboards read from. This is what makes your Looker Studio dashboard fast and accurate.
💡 This is what we do. We set up BigQuery, build the pipelines, write the transformations, and connect your dashboards — fully managed, no technical work on your end. Book a 20-minute discovery call — no pitch, just scoping.
BigQuery vs Google Sheets: when to use which
| Factor | Google Sheets | BigQuery |
|---|---|---|
| Data volume | Under 50,000 rows | Unlimited |
| Data sources | Manual exports/imports | Automated pipelines |
| Speed | Slows with data volume | Fast regardless of size |
| Collaboration | Easy | Needs dashboard layer |
| Historical data | Limited storage | Years of data, low cost |
| Automation | Fragile (scripts break) | Robust (built for this) |
| Cost | Free | Mostly free / very low cost |
If your sheet takes 30 seconds to load, has IMPORTRANGE formulas daisy-chaining six other sheets, and breaks when someone accidentally deletes a row — it’s time for BigQuery.
Common concerns (addressed)
“We don’t have a data team.” You don’t need one. Managed analytics services (like Chartica) handle the technical layer. Your team interacts with dashboards, not databases.
“It sounds expensive.” BigQuery itself costs almost nothing for most businesses. The cost is in setup and maintenance — which is why a monthly retainer with a managed service often makes more sense than hiring.
“What if something breaks?” Pipelines have monitoring and alerts. If a data source changes its API or stops syncing, you get notified and it gets fixed. With a managed service, that’s someone else’s problem.
“Can we still use our existing tools?” Yes. BigQuery doesn’t replace anything. It sits alongside your existing stack and pulls copies of the data.
Getting started (without hiring)
The fastest path from “we need this” to “it’s live” looks like:
- Audit current data sources (1-2 days). What tools do you use? Where does your important data live?
- Design the warehouse (2-3 days). What tables do you need? What questions should dashboards answer?
- Build pipelines (1 week). Connect sources to BigQuery via Fivetran or native connectors.
- Transform data (1 week). Write SQL models that clean and combine raw data.
- Build dashboards (1 week). Looker Studio dashboards reading from BigQuery.
Total: about three weeks from kickoff to live dashboards. That’s our standard timeline at Chartica for teams running 20+ data sources.
Know someone drowning in spreadsheets? Share this guide with them.
If this sounds like more work than you want to take on, that’s what we do at Chartica. Book a 20-minute discovery call — we’ll scope it out, no pitch.