Analytics Hub is a data exchange that allows you to efficiently and securely exchange data assets across organizations to address challenges of data reliability and cost. Curate a library of internal and external assets, including unique datasets like Google Trends, backed by the power of BigQuery.
Increase the ROI of data initiatives by exchanging data, ML models, or other analytics assets
Drive innovation with unique datasets from Google, commercial data providers, or your partners
Save time publishing or subscribing to shared datasets in a secure and privacy-safe environment
Analytics Hub builds on the scalability and flexibility of BigQuery to streamline how you publish, discover, and subscribe to data exchanges and incorporate into your analysis, without the need to move data.
Since 2010, BigQuery has supported always-live, in-place data sharing within an organization’s security perimeter (intra-organizational sharing) as well as data sharing across boundaries to external organizations, like vendor or partner ecosystems. Looking at usage over a one week period in September 2022, more than 6,000 organizations shared over 275 petabytes of data in BigQuery, not accounting for intra-organizational sharing. Analytics Hub makes the administration of sharing assets across any boundary even easier and more scalable, while retaining access to key capabilities of BigQuery like its built-in ML, real-time, and geospatial analytics.
Exchanges are collections of data and analytics assets designed for sharing. Administrators can easily curate an exchange by managing the dataset listings within the exchange. Rich metadata can help subscribers find the data they're looking for, and even leverage analytics assets associated with that data. Exchanges within Analytics Hub are private by default, but granular roles and permissions can be set easily for you to deliver data at scale to exactly the right audiences. Data publishers can now easily view and manage subscriptions for all their shared datasets. Administrators can now monitor the usage of Analytics Hub through Audit Logging and Information Schema, while enforcing VPC Service Controls to securely share data.
Shared datasets are collections of tables and views in BigQuery defined by a data publisher and make up the unit of cross-project/cross-organizational sharing. Data subscribers get an opaque, read-only, linked dataset inside their project and VPC perimeter that they can combine with their own datasets and connect to solutions from Google Cloud or our partners. For example, a retailer might create a single exchange to share demand forecasts to the thousands of vendors in their supply chain–having joined historical sales data with weather, web clickstream, and Google Trends data in their own BigQuery project, then sharing real-time outputs via Analytics Hub. The publisher can add metadata, track subscribers, and see aggregated usage metrics.
Explore the revamped search experience to browse and quickly find relevant datasets. In addition to easily finding your organization's internal datasets in Analytics Hub, this also includes Google datasets like Google Trends and Earth Engine, commercial datasets from our partners like Crux, and public datasets available in Google Cloud Marketplace.
Pricing for Analytics Hub is based on the underlying pricing structure of BigQuery, with the following distinctions for data publishers and data subscribe