BigQuery is Google Cloud's fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real time. With BigQuery, there's no infrastructure to set up or manage, letting you focus on finding meaningful insights using GoogleSQL and taking advantage of flexible pricing models across on-demand and flat-rate options.

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Resources

Explore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services.

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Training and tutorials

BigQuery for Data Warehousing

Learn best practices for extracting, transforming, and loading your data into Google Cloud with BigQuery.

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Training and tutorials

Preprocessing BigQuery Data with PySpark on Dataproc

Learn to create a data processing pipeline using Apache Spark with Dataproc on Google Cloud. It is a common use case in data science and data engineering to read data from one storage location, perform transformations on it and write it into another storage location.

Training

Training and tutorials

BigQuery For Data Analysis

Learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.

Training

Training and tutorials

BigQuery for Marketing Analysts

Get repeatable, scalable, and valuable insights into your data by learning how to query it using BigQuery.

Training

Training and tutorials

BigQuery for Machine Learning

Experiment with different model types in BigQuery Machine Learning, and learn what makes a good model.

Code sample

Code Samples

Python samples

Working with BigQuery with the Google Cloud Python client library

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Code Samples

Node.js samples

Samples for the Node.js client library sfor BigQuery

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Code Samples

C# simple sample

A simple C# program and code snippets for interacting with BigQuery

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Code Samples

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Last updated 2026-02-19 UTC.