Crux Informatics partners with Google Cloud to provide access to thousands of datasets

Crux Informatics (Crux) has partnered with Google Cloud to make it easier for Crux’s data suppliers to provide their data to customers. 

The Crux data catalog, which comprises thousands of datasets from over 100 traditional, alternative, and public data suppliers, will facilitate easier and faster data delivery to joint customers at no incremental charge.

Crux will enable delivery of authorised data sets directly into each client’s Google BigQuery environment, and will provide 24x7 monitoring, support and maintenance of all data pipelines into the clients’ Google Cloud environments. 

Data provisioned via Crux will be clean, actionable and analytics ready, enabling Google Cloud clients to confidently consume data that has undergone technical validations (eg, schema change), standardisations (eg, date consistency) and enrichments (eg, point-in-time timestamps). The data can be loaded into the client's BigQuery environment for immediate processing. 

“This partnership with Google Cloud will provide enormous benefit to joint customers who seek to receive this data cleanly, quickly and efficiently,” says Philip Brittan, CEO and co-founder of Crux. “At Crux, we are committed to helping data suppliers, technology platforms, and other organisations make data easily accessible and reliably available at scale. This partnership with Google Cloud removes unnecessary friction in the data supply chain and is a win-win for suppliers and consumers alike.”

“Today, businesses need access to the right data and the right analytics capabilities in order to inform important decisions,” sasaysid Anil Saboo, global financial services partnerships lead at Google Cloud. “We’re excited that Crux will make these datasets easily available on Google Cloud, making it simpler for customers, particularly those in the financial services industry, to analyse and manage this data in BigQuery.”

Google Cloud's customers can also employ Crux for more advanced data engineering needs, such as notifications and transformations. Forthcoming functionality includes advanced validations (eg, anomaly detection) and schema protection.