September 3, 2023

Setting Up a BigQuery Project: A Step-by-Step Guide – Part 1


So as an automotive dealer you’ve migrated to GA4, now what? GA4 has some limitations and the best way to overcome those is to setup a BigQuery project that will store your data and allow you to access it in a way that provides more value than GA4 alone. Google BigQuery is a powerful cloud-based data warehouse and analytics platform that allows you to store, query, and analyze massive datasets quickly and efficiently. To get started with BigQuery, you’ll need to set up a project within the Google Cloud Platform (GCP). In this step-by-step guide, we’ll walk you through the process of setting up a BigQuery project so you can begin harnessing the power of data analytics.

Step 1: Create a Google Cloud Platform Account

If you don’t already have a GCP account, the first step is to create one. Go to the Google Cloud Platform website and sign up. You may need to provide billing information, but Google often offers a free trial with a certain amount of credits to get you started.

Step 2: Access the Google Cloud Console

Once you have a GCP account, log in to the Google Cloud Console. This is your dashboard for managing all Google Cloud services, including BigQuery.

Step 3: Enable Billing

Before creating a BigQuery project, ensure that billing is enabled for your GCP account. Click on the billing tab in the left-hand navigation menu and set up your billing information. BigQuery usage will be billed separately, but you need an active billing account for the GCP project.

Step 4: Create a New GCP Project

In the Google Cloud Console, click on the project drop-down menu at the top of the screen. Then, click on “New Project.” Give your project a name and choose a billing account. Click “Create” to set up the new project.

Step 5: Enable BigQuery

Now that you have a GCP project, you need to enable BigQuery for it. In the Cloud Console, click on “Navigation Menu” (the three horizontal lines in the upper left) and select “BigQuery” from the “Big Data” section. If this is your first time using BigQuery in your GCP project, you may need to enable the BigQuery API.

Step 6: Configure Permissions

Next, configure the permissions for your project. Click on the “IAM & Admin” tab in the left-hand navigation menu. Here, you can add team members and assign roles like “BigQuery Admin” or “BigQuery User” based on their level of access. Ensure that you have the necessary permissions to use BigQuery effectively.

Step 7: Create and Load Datasets

With BigQuery enabled for your project, you can now create and load datasets. Datasets are containers for your tables and data. Click on your project name in the Cloud Console, navigate to “BigQuery,” and then click on “Create Dataset.” Follow the prompts to create your dataset, and then you can start loading data into it.

Step 8: Start Querying Data

You’re now ready to start querying data in BigQuery. Use the BigQuery web UI, command-line tools, or integrate BigQuery with various data visualization and analytics tools to analyze your data and gain valuable insights.


Setting up a BigQuery project is the first step toward harnessing the immense power of Google’s data analytics platform. With the right project structure, permissions, and datasets in place, you can efficiently store, query, and analyze your data to make informed decisions and gain valuable insights. Whether you’re a data analyst, data scientist, or business professional, BigQuery can help you unlock the potential of your data and drive your organization forward in the age of data-driven decision-making.

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