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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. Learn more

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Documentation resources

Find quickstarts and guides, review key references, and get help with common issues.
Explore self-paced training from Google Cloud Skills Boost, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services.
Training
Training and tutorials

Data Warehouse with BigQuery Jump Start Solution

Deploy and use a sample data warehouse with BigQuery.

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Training
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
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.

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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.

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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.

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Training
Training and tutorials

BigQuery for Machine Learning

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

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Use case
Use cases

Migrating data warehouses to BigQuery

Learn patterns and recommendations for transitioning your on-premises data warehouse to BigQuery.

Migration Patterns BigQuery

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Use case
Use cases

Visualizing BigQuery data in a Jupyter notebook

Use the BigQuery Python client library and Pandas in a Jupyter notebook to visualize data in a BigQuery sample table.

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Code Samples
Code Samples

Client: Create credentials with scopes

Create credentials with Drive and BigQuery API scopes.

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Code Samples
Code Samples

Client: Create credentials with application default credentials

Create a BigQuery client using application default credentials.

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Code Samples
Code Samples

Client: Create with service account key

Create a BigQuery client using a service account key file.

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Code Samples
Code Samples

Python samples

Working with BigQuery with the Google Cloud Python client library

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Code Samples
Code Samples

Node.js samples

Samples for the Node.js client library sfor BigQuery

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Code Samples
Code Samples

C# simple sample

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

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Code Samples
Code Samples

BigQuery and Cloud Monitoring on App Engine with Java 8

This API Showcase demonstrates how to run an App Engine standard environment application with dependencies on both BigQuery and Cloud Monitoring.

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Code Samples
Code Samples

All samples

Browse all samples for BigQuery

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