Learn more about privacy-centric data sharing with our recent announcement of BigQuery data clean rooms.

Jump to
Analytics Hub

Analytics Hub

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

Benefits

Save costs and efficiently share and exchange data 

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. 

Centralized management of data and analytics assets

Analytics Hub streamlines the accessibility of data and analytics assets. In addition to internal datasets, access public, industry, and Google datasets, like Looker Blocks, or Google Trends data.

Privacy-safe, secure data sharing with governance

Data shared within Analytics Hub automatically includes in-depth governance, encryption, and security from BigQuery, Cloud KMS, Cloud IAM, VPC Security Controls, and more.

Key features

The Analytics Hub difference

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, 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.

Analytics Hub architecture diagram

Privacy-centric sharing with data clean rooms

Create a low-trust environment for you and your partners to collaborate without copying or moving the underlying data right within BigQuery. This allows you to perform privacy-enhancing transformations in BigQuery SQL interfaces and monitor usage to detect privacy threats on shared data. Benefit from BigQuery scale without needing to manage any infrastructure and built-in BI and AI/ML. Explore use cases for data clean rooms.

Curated exchanges with subscription management and governance

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.

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 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.

Analytics Hub diagram for web

Search and discovery for internal, public, or commercial datasets

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.

Equifax logo
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.

Kumar Menon, SVP Data Fabric and Decision Science, Equifax

Learn more

Documentation

Documentation

Architecture

Introduction to Analytics Hub

With Analytics Hub, you can discover and access a data library curated by various data providers. Explore architecture for publisher and subscriber workflows.

Google Cloud Basics

Manage data exchanges

Get started by learning how to create, update, or delete a data exchange and manage Analytics Hub users.

Google Cloud Basics

Manage listings

A listing is a reference to a shared dataset that a publisher lists in a data exchange. Learn how to manage listings as an Analytics Hub publisher.

Not seeing what you’re looking for?

Pricing

Simple and logical pricing

Pricing for Analytics Hub is based on the underlying pricing structure of BigQuery, with the following distinctions for data publishers and data subscribers.

Organizations publishing data into an exchange pay for the storage of that data according to BigQuery storage pricing.

Organizations subscribing to data from an exchange only pay for query processing from within their organization, and according to their BigQuery pricing plan (flat-rate or on-demand).

For detailed pricing information, please view the BigQuery pricing guide.

Partners

Thousands of datasets made available via public and commercial data providers

If you're interested in becoming a data provider or learning about our Data Gravity initiative, please contact Google Cloud sales


This product is in early access. For more information on our product launch stages, see here

Take the next step

Start building on Google Cloud with $300 in free credits and 20+ always free products.

Google Cloud
  • ‪English‬
  • ‪Deutsch‬
  • ‪Español‬
  • ‪Español (Latinoamérica)‬
  • ‪Français‬
  • ‪Indonesia‬
  • ‪Italiano‬
  • ‪Português (Brasil)‬
  • ‪简体中文‬
  • ‪繁體中文‬
  • ‪日本語‬
  • ‪한국어‬
Console
Google Cloud