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New Google tools aim to simplify data analytics lifecycle

Google Cloud unveiled a trio of new tools, aimed at enabling users to work through the entire analytics workflow, during its virtual Data Cloud Summit.

Google Cloud unveiled a trio of tools on Wednesday designed to provide customers with a unified cloud data platform to use throughout the analytics process so they can act on their data in real time.

The tech giant introduced Analytics Hub, Dataplex and Datastream during the inaugural Data Cloud Summit, a virtual user conference.

All are currently in preview.

Google said it devised the capabilities to be used in concert with one another to give organizations the ability to handle the entire analytics process, from data capture to data management, and then to insight and action. Together, they help free organizations from data silos to ultimately make data-driven decisions as soon as new data is available, according to the vendor.

"We are trying to make working with data simple by turning data into an ability," said Gerrit Kazmaier, general manager and vice president for databases, data analytics and Looker at Google Cloud. "We fundamentally want to change the way companies think about data from a technology-centric view to an ability-centric view. That requires a set of interconnected skills to work together."

Analytics Hub is a portal where customers can securely create, curate and manage analytics assets such as dashboards and machine learning models that they can then share both across their organizations and with trusted outside recipients to enable real-time decision-making.

The tool is in addition to the sharing capabilities in BigQuery, Google's cloud-based big data analytics web service.

The Google Analytics Hub workflow.
A diagram displays the Google Analytics Hub workflow.

Dataplex is an environment in which organizations can automate their data management. Designed to bring Google Cloud and third-party open source technologies together, it enables organizations to curate, secure, integrate and analyze their data in a single location and includes automation features to help ensure data quality and governance.

Datastream, finally, is a serverless change data capture and replication service that enables customers to capture data in real time and replicate data streams from any data source.

Individually, each of the three new tools addresses a need for users. The way Analytics Hub, Dataplex and Datastream were developed to work together, however, is where the real effectiveness in Google's new tools could lie, according to Mike Leone, senior analyst at Enterprise Strategy Group.

"The three new capabilities together represent a scenario where the whole is greater than the sum of its parts," he said. "With Datastream, organizations will have faster access to real-time and relevant data.

Analytics Hub is incredibly powerful to me. We've seen the rise of data exchanges, making highly curated data available to others. Analytics Hub takes [that] a step farther by offering an analytics exchange.
Mike LeoneSenior analyst, Enterprise Strategy Group

"With Dataplex, the data can then be intelligently managed and made available in a seamless way, enabling data stakeholders to access and analyze high quality data with confidence."

But it's the sharing of completed data assets such as dashboards and machine learning models enabled by Analytics Hub that most stands out, Leone continued.

"Analytics Hub is incredibly powerful to me," he said. "We've seen the rise of data exchanges, making highly curated data available to others. Analytics Hub takes [that] a step farther by offering an analytics exchange. Empowering users [to share] dynamic dashboards or pre-trained ML models will go a long way in enabling customers to gain value faster from data initiatives and analytics investments."

In addition to Analytics Hub, Dataplex and Datastream, Google Cloud unveiled a host of other new analytics tools during its Data Cloud Summit. They include:

  • BigQuery Omni for Microsoft Azure and Looker for Microsoft Azure, which build on Google Cloud's approach to enabling multi-cloud deployments;
  • BigQuery ML Anomaly detection to enable customers to detect abnormalities in their data using BigQuery's built-in machine learning capabilities; and
  • Dataflow, a streaming analytics capability that enables users to embed augmented intelligence and ML capabilities.

In addition, Google Cloud said it is lowering the entry price for Cloud Spanner, its fully managed relational database, with the introduction of what it calls granular instance sizing.

Looker for Microsoft Azure and BigQuery Anomaly Detection are now generally available, while BigQuery Omni for Microsoft Azure, Dataflow and the new entry price for Cloud Spanner are in the works.

And like Analytics Hub, Dataplex and Datastream, each of the additional Google Cloud tools were designed to fit in with the concept of making data an ability rather than a technology, according to Kazmaier.

"All these areas, from our database to data analytics and to Looker, are going to be rewired to build that connective tissue across the data lifecycle," he said. "Fundamentally, we believe this is what makes working with data simple."

Enterprise Strategy Group is a division of TechTarget.

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