17.4. SQL Workspace in BigQuery

Welcome to the SQL Workspace in BigQuery, where we'll explore how to create projects, datasets, and tables within Looker Studio.

Hierarchy in BigQuery

BigQuery has a hierarchy similar to Google Sheets. In Google Sheets, you have an account with multiple spreadsheets nested inside. Similarly, in BigQuery:

1. Projects act like your account
2. Datasets are contained within projects
3. Tables and views are housed within datasets

Creating a Dataset

Since our project is currently empty, let's create a dataset:

1. Click on your project name (e.g., profitable_dashboards_bq)
2. Click the + icon to create a new dataset
3. Give your dataset an ID (e.g., query_analysis)
4. Choose the data location (US or EU servers)

Now you have both a project and a dataset.

Naming Conventions

There are various naming conventions for datasets, tables, and fields in BigQuery and SQL:

• Snake case: all lowercase characters with underscores separating words (e.g., query_analysis)
• Camel case: starts with lowercase; each new word begins with an uppercase letter (e.g., queryAnalysis)
• Pascal case: every word starts with an uppercase letter (e.g., QueryAnalysis)

I recommend using snake case since it's widely used by Google and others in advanced data processing scenarios like GA4 to BigQuery data transfer.

Importing Data

Now that we have our dataset created, it's time to bring some data into it! In the next lesson we’ll cover how to bring a google sheet into BigQuery.

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