At the third annual Google Data Cloud and AI Summit, we shared how data analytics and insights continue to be a key focus area for our customers and how we’re accelerating their data journeys through new product innovations and partner offerings.
A big part of that is helping customers turn their data into insights faster using differentiated datasets from partners and integrating them into their AI/ML workflows. We recently announced our partnership with Crux to add over 1,000 new datasets on Analytics Hubto provide customers with access to a rich ecosystem of data to enrich first-party data assets and accelerate time to value and scalability with real time insights. There will be an initial focus on Financial Services, ESG, and Supply Chain, but we plan to increase this to 2,000 datasets later this year. These datasets are critical to our customers who execute highly process-intensive analytics workloads for trading, planning, and risk calculations.
An industry leader, Dun & Bradstreet, will also make much of its catalog available on Analytics Hub and listed on the Google Cloud Marketplace. This will enable customers to achieve the same benefits they receive for SaaS purchases in the Marketplace, including simplified procurement, consolidated billing, and financial incentives.
“We are excited to build upon our ten-year relationship with Google Cloud and both companies’ commitments to deliver innovative opportunities to our mutual customers,” said Ginny Gomez, President, Dun & Bradstreet North America. “By making D&B datasets and products available in the Google Cloud Marketplace, we are making it easier for our customers to access and utilize this critical data, while also helping to provide a frictionless procurement process for customers to use their committed Google Cloud spend.”
When you purchase and subscribe to a dataset in the Google Cloud Marketplace, the data is immediately accessible via your BigQuery environment via Analytics Hub, without ingress, storage charges, or wait times. This allows your project teams to leverage Google Cloud AI/ML, BigQuery, and other third-party innovations to get valuable insights from datasets with ease. This is a commercial expansion on the hundreds of public and free datasets already listed in the Google Cloud Marketplace.
Analytics Hub is 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, as well as data sharing across boundaries to external organizations. Analytics Hub makes the administration of sharing assets across boundaries even easier and more scalable, while retaining access to key capabilities of BigQuery like its time-tested sharing infrastructure, and built-in ML, real-time and geospatial analytics.
These datasets on Marketplace also benefit from BigQuery’s advantages:
Scale: BigQuery is an exabyte-scale data warehouse that can handle even the most demanding data sharing needs. It grows with your data needs including auto scaling capabilities.
Security: BigQuery is built on Google’s secure infrastructure and offers various security features to protect your data. Data is always encrypted and PII data discovery services can be directly used to improve the security of the data.
Freshness: BigQuery data can be shared without moving it, this means you can join shared data with your own data with no need to implement expensive ETLs to bring the data from the providers
Cost-effectiveness: BigQuery provides different billing models so each workload can make use of the data providing the best price/performance.
At Google Cloud, we believe data and AI have the power to transform businesses and unlock the next wave of innovation. We are excited to share that customers can now procure new data assets on the Google Cloud Marketplace to accelerate their business decisions and drive new innovations. Customers interested in these datasets, can request a custom quote, or more information by clicking Contact Sales on the Marketplace product page and completing the inquiry form.