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.
A GitHub Action for installing and configuring the gcloud CLI.
This project uses Google Analytics 4 BigQuery Exports as its source data, and offers useful base transformations to provide report-ready dimension & fact models that can be used for reporting purposes, blending with other data, and/or feature engineering for ML models.
CLI tool to easily Decorate BigQuery table name
Printing profiles for BQ printers
Printing profiles for BQ Witbox 2, BQ Hephestos 2, FLSUN QQ-S PRO and (soon) FLSUN Prusa i3 C Plus 3D Printers
App Android para Zowi impreso en 3D
Creating pipelines using Python3 and Apache Airflow to load tables into Google Big Query Dataware House
3D Printer Profile for bq Hephestos 2 used with Simplify3D
Criação de segmentação de publico via SQL para nova feature do enjoei de comissão reduzida
Linux Kernel source code for the device bq Aquaris M10 4G
Released May 19, 2010