17.3. Getting Data into BigQuery
In this lesson, we'll go over how to create a data pipeline, review raw data from Google Sheets, and import that data into BigQuery. Although we won't have time to cover everything in depth, this example is designed to demonstrate as many features in BigQuery as possible that you'll likely use when working with Looker Studio.
Reviewing Data from Google Sheets
We have two sets of data in Google Sheets obtained using Supermetrics:
Google Search Console Data: Search queries, landing pages, impressions, and clicks.
Google Analytics Data: Landing page data source medium with sessions, goal completions, and total goal value.
Our goal is to import these datasets into BigQuery.
Setting up a BigQuery Project
First things first - navigate to the BigQuery console. If you don't have an account yet, follow the prompts to create one and enter your billing information.
Once you're logged in, you'll notice that BigQuery is structured around projects. Each project governs access to different resources within Google Cloud (including BigQuery) and handles billing.
To create a new project:
Click on the project dropdown at the top of the page.
Select New Project.
Give your project a name (e.g., Profitable Dashboard BQ).
Choose your organization (this will inherit billing settings from it).
Wait for a moment while BigQuery creates your new project.
Accessing BigQuery within Your Project
Now that your project has been created:
Select it from the list of projects.
On the right-hand side of the screen, find BigQuery under one of the tools available in Google Cloud Platform.
Pin it at the top for quick access.
Most of your time in BigQuery will be spent within the SQL Workspace.
Exploring the SQL Workspace
Now that we're in the SQL Workspace, we can start building our data pipeline and importing the data from Google Sheets. In future lessons, we'll dive deeper into using BigQuery and Looker Studio to manipulate and visualize this data.
