Google Cloud is a suite of cloud computing services. It covers storage, data analytics, machine learning, artificial intelligence, and much more. Google Cloud Platform, often called GCP, is the infrastructure that hosts all of these services.
If you use Google BigQuery, you are already using Google Cloud. BigQuery is one service within the broader Google Cloud Platform.
The Most Important Google Cloud Services for Marketing Teams
Google Cloud offers hundreds of services. Most of them are for software engineers and data scientists. But a handful are directly relevant to marketing teams.
Here are the six you are most likely to encounter:
- BigQuery: a data warehouse for storing and querying large volumes of marketing data. This is the core tool for marketing analytics at scale.
- Looker Studio: a free dashboarding and reporting tool. It connects directly to BigQuery and lets you build visual reports without writing SQL.
- Cloud Storage: a service for storing files and objects. Useful for storing raw data files, exports, and backups.
- Compute Engine: virtual machines in the cloud. Relevant if your team runs custom data processing scripts that need a server.
- Cloud SQL: a managed relational database service. Useful for teams that need a traditional database alongside their data warehouse.
- Vertex AI: a machine learning platform. Relevant for teams building predictive models on top of their marketing data.
For most marketing teams, BigQuery and Looker Studio are the two Google Cloud services that matter most.
How Google Cloud Relates to BigQuery
Think of Google Cloud as the umbrella. Under that umbrella, you have dozens of services, each built for a specific purpose. BigQuery is one of those services, built specifically for storing and querying large datasets.
When you create a Google Cloud account, you get access to all of these services, including BigQuery. You pay only for what you use, and BigQuery has a permanent free tier that covers most marketing teams.
Why Google Cloud Matters for Marketing Data
Google Cloud is where your marketing data warehouse lives. When you connect your ad platforms, your CRM, and your analytics tools to BigQuery, all of that data sits on Google Cloud infrastructure.
That means:
Your data is stored securely on Google’s servers.
Your queries run on Google’s computing infrastructure, not on your laptop.
Your data is accessible from anywhere, by any tool that connects to BigQuery.
You do not manage servers, storage, or backups. Google handles all of that.
Getting Started With Google Cloud
To use BigQuery, you need a Google Cloud account. The process takes about five minutes:
Go to cloud.google.com and sign in with your Google account.
Create a new project. A project is a container for all the resources you create in Google Cloud.
Enable the BigQuery API within your project.
Set up billing. Even though BigQuery has a free tier, Google Cloud requires a billing account. You will not be charged unless you exceed the free limits.
Once your account is set up, you are ready to create datasets and tables in BigQuery and start loading your marketing data.
Connecting Your Marketing Data to Google Cloud
Porter Metrics connects your marketing data sources, including Meta Ads, Google Ads, TikTok, LinkedIn, GA4, HubSpot, and Shopify, directly to BigQuery in Google Cloud. You do not write code or manage infrastructure. You connect your accounts, select your data, and Porter loads everything into BigQuery automatically.
Ready to connect your marketing data to BigQuery?
Porter Metrics makes it easy to sync all your sources — no code required.