Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
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Updated
May 21, 2024 - Python
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.
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Common solutions and tools developed by Google Cloud's Professional Services team. This repository and its contents are not an officially supported Google product.
Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery https://goo.gl/oY5BCQ
the portable Python dataframe library
Simple Python client for interacting with Google BigQuery.
Swirl is open-source software that uses AI to simultaneously search multiple content and data sources, finds the best results using a reader LLM, then prompts Generative AI, enabling you to get answers from your own data.
🎣 List of `pre-commit` hooks to ensure the quality of your `dbt` projects.
Dataproc templates and pipelines for solving simple in-cloud data tasks
ETL (extract, transform and load) tools for ingesting Polygon blockchain data to Google BigQuery and Pub/Sub
Data Foundation - Google Cloud Cortex Framework
Cloud-native, data onboarding architecture for Google Cloud Datasets
Community Security Analytics provides a set of community-driven audit & threat queries for Google Cloud
First Party data integration solution built for marketing teams to enable audience and conversion onboarding into Google Marketing products (Google Ads, Campaign Manager, Google Analytics).
Reference framework for building data workflows provided by Google. Accelerates authentication, logging, scheduling, and deployment of solutions using GCP. To borrow a tagline.. "The framework for professionals with deadlines."
Generates the BigQuery schema from newline-delimited JSON or CSV data records.
Released May 19, 2010