Valuable analytics assets in a centralized hub
Analytics Hub streamlines the accessibility of data and analytics assets from internal teams, from public or industry providers, and from Google; e.g., pre-built Looker Blocks code, or Google Trends data.
A powerful platform for efficient exchanges
Analytics Hub builds on the scalability and flexibility of BigQuery to streamline how you publish, discover, and subscribe to data or analytics exchanges, and incorporate them into your existing workflows.
Built on a decade of data sharing in BigQuery
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, e.g., in your vendor or partner ecosystem. Looking at usage over a one week period in April of this year (2021), more than 3,000 organizations shared over 200 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.
Curation and self-service through exchanges
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.
A sharing model for scalability, security, and flexibility
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 1,000’s 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.
Delivering business value and innovation through secure data sharing
“We are excited to partner with Google to leverage Analytics Hub and BigQuery to deliver data to over 400 statisticians and data modelers as well as securely sharing data with our partner financial institutions.”