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Analytics Hub efficiently and securely exchanges data analytics assets across organizations to address challenges of data reliability and cost. Create and access a curated library of internal and external assets, including unique datasets like Google Trends, backed by the power of BigQuery.

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    Drive innovation with unique datasets from Google, commercial data providers, or your partners

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    Exchange data, ML models, or other analytics assets to increase the ROI of data initiatives

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    Easily publish or subscribe to shared datasets in an open, secure, and privacy-safe environment


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.

Robust security controls, always privacy-safe

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, 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.

Analytics Hub diagram for web

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.”

Kumar Menon, SVP Data Fabric and Decision Science, Equifax
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What's new

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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.


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