Google launches preview of ‘integrated data cloud’ to help unify multicloud data

Google LLC is doubling down on big data at its inaugural Data Cloud Summit today with the launch of three new cloud services that it says will combine to create an “integrated data cloud” that spans multicloud environments, helping enterprises become more data-driven.

The new services include Dataplex for intelligent data management, Analytics Hub, which is meant to enable data access and sharing, and Datastream to enhance data replication across multicloud environments. Together, Google says, the new services can help to break down the age-old problem of data silos so companies can manage multicloud data, analyze it more easily and obtain insights in real time to improve their decision-making and innovation.

Available in preview starting today, Dataplex provides an intelligent data fabric plus an integrated analytics experience that enables customers to curate, secure, integrate and analyze data at large scale, Google said.

In a press briefing, Irina Farooq, Google’s director of product management for data analytics, said one of the biggest challenges with enterprise data is that it is and always will be distributed. That creates a lot of tension for information technology teams that need to integrate that data, she said, since they must implement various connecting tools and worry about security, standardization and governance across the data warehouses, data lakes and databases they use.

“Dataplex is an intelligent data fabric that allows organizations to centrally manage, monitor and govern their data across all those data stores,” Farooq said. “[It provides] an integrated analytics experience, intelligent data management and centralized security and governance.”

By automating those tasks, data scientists will be able to unify and manage their data without any movement or duplication, Farooq explained.

Once customers have a more unified data experience, they’ll most likely want to be able to share that information across the different clouds, services and applications they use and that’s where Datastream comes in. Also available now in preview, Datastream is a serverless Change Data Capture and replication tool that’s able to take live data streams from Oracle and MySQL databases and replicate these in services such as Google BigQuery, Cloud SQL, Google Cloud Storage and Cloud Spanner. It’s really just an easier way to connect data from one store to another in real-time, said Andi Gutmans, general manager and vice president of engineering for databases at Google Cloud.

Change Data Capture is a technique used by enterprises to eradicate data silos. It works by tracking any changes in a source dataset and transferring them to the target dataset, where the information from the source is replicated. This is supposed to happen in real time or at least very close to real time, but Gutmans said it can be difficult to implement.

“Change Data Capture allows fast and reliable business decisions, flexible microservices for event-based applications and synchronized heterogeneous databases,” he said. “But it’s very hard to manage. Datastream can replicate data with minimal latency, scale up and down, and has flexibility with Google Cloud’s data integration solutions.”

The final piece of Google’s new data management puzzle is Analytics Hub, which will be available soon in preview. The idea with this is that companies will be able to create, curate and manage their analytics exchanges more securely and in real time, Google said. It will enable customers to share both data and insights and also things such as dynamic dashboards and machine learning models, both inside and outside their organization.

Debanjan Saha (pictured), general manager and vice president of engineering for data analytics at Google Cloud, said Analytics Hub will make it possible for users to query data wherever its stored and then share whatever insights they discover.

Saha explained that it helps to overcome a number of challenges with traditional data sharing ecosystems, such as their high costs, fragile data pipelines, late-arriving data assets, governance, security and privacy workflows, and loss of control over data. At the same time, Analytics Hub enables companies to combine their own data with third-party datasets from commercial, industry and public sources, he said.

“It ushers in a new world for data insight and sharing,” Saha said.

The services aren’t all entirely new, Saha added in response to a question, with Google integrating existing and new services to provide a more unified view of data and the ability to use it.

Analyst Holger Mueller of Constellation Research Inc. told SiliconANGLE that the developments show how Google continues to double down on multicloud support, catering to some of the more gnarly data challenges faced by enterprises today.

“It’s good to see that Google delivering new innovations with Dataplex, Analytics Hub and Datastream, with strong multicloud ambitions and capabilities,” he said.

The launch of the new services was announced alongside a host of updates to Google’s existing portfolio of data and analytics tools. They include preview availability of BigQuery Omni on Microsoft Azure and general availability of Looker for Microsoft Azure, which means customers will be able to use Google’s tools to analyze data in Microsoft Corp.’s Azure cloud.

Also hitting general availability today is BigQuery ML Anomaly Detection, a service that detects abnormal patterns in data to detect fraud and other issues.

Tom Galizia, global chief commercial officer for the information technology consulting firm Deloitte Touche Tohmatsu Ltd., said he was looking forward to helping organizations implement Google’s new services.

“What is truly powerful here is that Google Cloud solves for disparate and bespoke systems housing hard-to-access siloed data with enhanced data experiences,” Galizia said. “They’ve also simplified implementation and management for better decision making. We are truly excited to realize the market potential with Google Cloud’s innovations for building data clouds.”

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