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Google Cloud partners with Databricks for enterprise analytics

The deal means Databricks can be deployed in fully containerised cloud environments for the first time

Google Cloud has announced a new partnership with analytics firm Databricks to offer data-driven services to enterprise customers. 

The deal means businesses can now use Databricks to create a lakehouse capable of data engineering, data science, machine learning, and analytics on Google Cloud’s elastic network.

This will include integrations with BigQuery and Google's Kubernetes Engine (GKE), opening up the chance to deploy Databricks in fully containerised cloud environments for the first time, according to Google. 

The deal is further evidence of Google's cloud strategy to prioritise analytical tools and processes, which has been a key driver of its most recent acquisitions and new offerings

"Businesses with a strong foundation of data and analytics are well-positioned to grow and thrive in the next decade," the Google Cloud CEO, Thomas Kurian, said. 

"By combining Databricks capabilities in data engineering and analytics with Google Cloud's global, secure network - and our expertise in analytics and delivering containerised applications - we can help companies transform their businesses through the power of data."

The pandemic has transformed businesses in ways that most experts thought technologies would do and as such, these technologies are now at the forefront of the so-called new normal. The key is scalability, specifically the ability to increase or reduce the use of certain services depending on the user's needs. 

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Google suggests its deployment of Databricks will offer a customisable service for analytics that can be customised to suit a businesses' needs. The tight integration with Google BigQuery gives customers the freedom to choose a number of data analytics services in a range of sizes.

Similarly, Databricks for containerised workloads highlights one of the most rapidly evolving ways of working within the cloud. Kubernetes is swiftly becoming the de facto orchestration system for enterprise workloads and most AI and machine learning tools. 

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