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BigQuery interactive walkthroughs and videos

BigQuery interactive walkthroughs

The following interactive walkthroughs help you get started with BigQuery.

Before you begin

In the Cloud de Confiance console, on the project selector page, select or create a Cloud de Confiance project.
Roles required to select or create a project
- Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
- Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.
Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector
Enable the BigQuery API.
Roles required to enable APIs
To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.
Enable the API

For new projects, the BigQuery API is automatically enabled.
Optional: Enable billing for the project. If you don't want to enable billing or provide a credit card, the steps in this document still work. BigQuery provides you a sandbox to perform the steps. For more information, see Enable the BigQuery sandbox.
Note: If your project has a billing account and you want to use the BigQuery sandbox, then disable billing for your project.

These walkthroughs are launched in the Cloud de Confiance console. Click the links to launch the interactive tutorial.

Title	Description
Loading and querying data
Query a public dataset in BigQuery Studio	Use the BigQuery sandbox to query and visualize data in a public dataset.
Load and query data using BigQuery Studio	Use BigQuery Studio to create a dataset, load data, and query the data.
Load and query data with the `bq` command-line tool	Use the BigQuery command-line tool to create a dataset, load data, and query the data.
Import data from Cloud Storage to BigQuery	Use the Cloud de Confiance console to import data from Cloud Storage into BigQuery, and query the data.
Workload management
Get started with reservations	Use the Cloud de Confiance console to purchase slots, create a reservation, and assign a project to a reservation.
AI
Write queries with Gemini assistance	Use Gemini AI-powered assistance in BigQuery to help you query your data using SQL queries and Python code.
Client libraries
C# tour	Query a public dataset with the BigQuery C# client library.
Go tour	Query a public dataset with the BigQuery Go client library.
Java tour	Query a public dataset with the BigQuery Java client library.
Node.js tour	Query a public dataset with the BigQuery Node.js client library.
PHP tour	Query a public dataset with the BigQuery PHP client library.
Python tour	Query a public dataset with the BigQuery Python client library.
Ruby tour	Query a public dataset with the BigQuery Ruby client library.

BigQuery videos

The following series of video tutorials help you learn more about BigQuery. For more Cloud de Confiance by S3NS videos, subscribe to the Google Cloud Tech YouTube channel.

Title	Description
Product overviews
BigQuery in a minute (1:26)	A brief overview of BigQuery, Google's fully-managed data warehouse.
BigQuery ML in a minute (1:40)	A brief overview of BigQuery ML. With BigQuery ML, you can train, evaluate, and run inference on models for tasks such as time series forecasting, anomaly detection, classification, regression, clustering, dimensionality reduction, and recommendations.
AI
Introduction to Gemini AI and data analytics in BigQuery (3:42)	An introduction to Gemini in BigQuery which provids AI and data analytics capabilities that help streamline your workflows across the entire data lifecycle.
Use BigQuery & Gemini AI for data analytics (7:00)	An overview of how Gemini models can help you generate new insights, enrich your datasets, and even analyze multimodal content including images, videos, and text.
Introducing BigQuery data engineering agents (6:19)	An introduction to BigQuery Data Engineering Agents that help data analysts save time coding, schema mapping, and creating metadata.
BigQuery data canvas overview (6:03)	An overview of AI-powered BigQuery data canvas. This natural language centric tool simplifies the process of finding, querying, and visualizing your data.
Querying and visualizing data
Introducing pipe syntax in BigQuery and Cloud Logging (5:00)	BigQuery's pipe syntax offers a more intuitive way to structure your code. Learn how pipe syntax simplifies both exploratory analysis and complex log analytics tasks, helping you gain insights faster.
Visualizing BigQuery geospatial data in Colab (10:00)	BigQuery lets you store and analyze geospatial data using standard SQL, and bringing that data into a Colab notebook gives you the flexibility to combine BigQuery's power with popular Python visualization libraries.
Visualize BigQuery data with Looker (3:00)	An overview of how to seamlessly connect to and visualize your BigQuery data using Looker's user-friendly interface and powerful semantic modeling capabilities.
BigQuery storage
A tour of BigQuery tables (6:55)	An overview of the different types of tables in BigQuery, including managed tables, external tables, and virtual tables with logical and materialized views.
How does BigQuery store data? (8:19)	An introduction to how BigQuery stores data so you can make informed decisions on how to optimize your BigQuery storage. This includes an overview of partitioning and clustering.
Monitoring and logging
Monitoring in BigQuery (7:43)	An overview of how monitoring your data warehouse can optimize costs, help you pinpoint which queries need to be optimized, and audit both data sharing and access.