The rapid pace of digital transformation and the growing adoption of a hybrid cloud infrastructure has added layers of complexity and cost to data management.

The solution is the development of an intelligent data fabric to enable automation and a frictionless access of information, according to Madhu Kochar (pictured), vice president of offering management, data and AI, at IBM. This is what is behind the next generation of IBM Cloud Pak for Data.

“An intelligent data fabric is what weaves together and automates data and AI lifecycle over anything, and over anything means any data, any cloud, anywhere,” she said. “What you get with this is that you are able to then unlock totally new insights from unified data, you are able to democratize your trusted data usage across more people, you unleash truly productivity, you reduce cost and risk, and you make AI for business easier.”

Kochar spoke with John Furrier, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during IBM Think. They discussed the challenges of managing an increasing amount of distributed data, how an intelligent data fabric can help enterprises in this scenario, and the characteristics of the next generation of IBM Cloud Pak for Data. (* Disclosure below.)

Capabilities for seamless automation

The next generation of IBM Cloud Pak for Data brings three features that have been combined as part of the intelligent data fabric to seamlessly automate how unified data is accessed in a hybrid environment. The number one feature is AutoPrivacy, which means how enterprises can automate and enforce universal data and usage policies across hybrid data and cloud ecosystems, and how to express it to users in business terms.

“This is going to further simplify risk mitigation across an organization of self-serve data consumers,” Kochar explained.

The second top capability and what Kochar considers the “brain” of this system is the AutoCatalog, that is, the automation of how data is discovered, cataloged and enriched for users.

“The third thing very critical is what we call AutoSQL,” she said. “This is how you’re going to automate how you access, update and unify data spread across distributed data and cloud landscapes without the need of actually doing any data movement or replication.”

These capabilities are built on top of what IBM calls the AutoAI feature, which automatically analyzes data and generates customized model pipelines for predictive modeling problem. The new generation of IBM Cloud Pak for Data is an update from the previous version, announced about three years ago.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of IBM Think. (* Disclosure: TheCUBE is a paid media partner for IBM Think. Neither IBM, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE