100+ SQL Scripts - PostgreSQL, MySQL, Oracle, Google BigQuery, MariaDB, AWS Athena. DBA, Analytics, DevOps, performance engineering. Google BigQuery ML machine learning classification.
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Feb 3, 2026 - Shell
Google BigQuery enables companies to handle large amounts of data without having to manage infrastructure. Google’s documentation describes it as a « serverless architecture (that) lets you use SQL queries to answer your organization’s biggest questions with zero infrastructure management. BigQuery’s scalable, distributed analysis engine lets you query terabytes in seconds and petabytes in minutes. » Its client libraries allow the use of widely known languages such as Python, Java, JavaScript, and Go. Federated queries are also supported, making it flexible to read data from external sources.
📖 A highly rated canonical book on it is « Google BigQuery: The Definitive Guide », a comprehensive reference.
Another enriching read on the subject is the inside story told in the article by the founding product manager of BigQuery celebrating its 10th anniversary.
100+ SQL Scripts - PostgreSQL, MySQL, Oracle, Google BigQuery, MariaDB, AWS Athena. DBA, Analytics, DevOps, performance engineering. Google BigQuery ML machine learning classification.
An example Dataform project to load and transform the publicly available dataset from IMDB.
Business model representation automation
GCP_Data_Enginner
GitHub Action for writing data into BigQuery from within a Github workflow
An example Dataform project which will use the publicly available Movielens dataset to demonstrate how to upload your product catalog and user events into either the Google Cloud Retail API or Google Cloud Discovery Engine and train a personalised product recommendation model.
An example Dataform project to load and transform the publicly available dataset from H&M Group into a format which could be imported into Discovery AI for Retail or Vertex AI Search and Conversation, , allowing you to train a retail recommendations model.
A Data Engineering ELT pipeline to extract, analyse and automate Greenhouse gas emission Analytics
DBT execution from Cloud Composer. BigQuery is used for main DWH and Compute Engine is built for dbt execution.
Copy table from one dataset to another in google big query using bash script
The Data Pipeline using Google Cloud Dataproc, Cloud Storage and BigQuery
☁️ Deploy stateless Node.js applications as serverless containers on Cloud Run for efficient, scalable, and cost-effective cloud computing.
A Bash script for exporting all tables from a BigQuery dataset to local storage
Released May 19, 2010