Data Commons in BigQuery
The Data Commons repository is available as BigQuery tables in the Analytics Hub.
For an introduction to Analytics Hub, see documentation here. In these pages you can learn how to use the Data Commons tables and find sample SQL queries.
In a Nutshell: What’s Different about Data Commons
Data Commons (DC) synthesizes a single graph from a large number of sources into a single data source. It resolves references to the same entities (such as cities, counties, organizations, etc.) across different datasets so that users can access data about a particular entity aggregated from different sources without data cleaning or joining.
Today, DC contains over 3B time series about 90k variables about around 3M entities. This single data source has been pulled together from across many thousands of ‘traditional’ tables. This document briefly goes over how you can determine what data is available, explore it and construct BQ queries to retrieve it.
We first go over some DC basics and then give a sequence of examples of increasing complexity. Every DC Map visualization and Time Series visualization also links to the corresponding BQ query for obtaining the data used in that visualization