Big data analytics is the fuel of future business, providing the power behind advances in machine learning, artificial intelligence, and other hot trends being discussed in boardrooms across the globe. Yet, as enticing as these new technologies are, many in the C-suite have been cautious about entrusting their organization’s sensitive data to the public cloud where information can be shared, analyzed and even breached in real time.

“There’s a lot of fear associated with [the cloud],” said Christian Rodatus (pictured), chief executive officer of Datameer Inc. “It’s data governance; it’s security; it’s data privacy.”

Rodatus sat down with Peter Burris, (@plburris), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, for a CUBE Conversation at theCUBE’s studio in Palo Alto, California. They discussed the increase in hybrid cloud adoption by large enterprises and the implications on big data analytics. (* Disclosure below.)

The past year has seen fast movement to hybrid cloud

Many of Datameer’s customers are in industries reluctant to trust their data to the cloud, such as business and financial services, insurance, healthcare and telecommunications. Analytics was important to these companies long before big data and cloud computing came along, but they were tentative to entrust strategic, sensitive data to a new industry with untested infrastructure, Rodatus pointed out.

In the past year, however, these industries have been moving to the cloud, and not just moving, but moving fast. “Since 12, 15 months, the transition in the analytics market … how they are accelerating cloud adoption, how they move analytic workloads to the cloud … has been stunning,” Rodatus stated.

The most touted benefits of moving analytic workloads into the cloud are lower costs and agility, but freedom from waiting on the information technology department to create and run complicated models is a plus for employees who just want results ASAP.

“They want to do this on their own and create their own views, depending on their analytic workflow in a very rapid, rapid way,” Rodatus said.

Datameer’s analytics platform provides a solution framework that helps clients transition on-premises analytic workloads into the cloud while keeping the enterprise grade features that they’re familiar with, Rodatus explained. Security is provided through auditing and data lineage features that track how data is being sourced and manipulated, while curation, discovery and analysis tools democratize employee access to all data.

“This is really what helps them build rapid analytic applications that provide a lot of value and benefits for their business processes,” Rodatus said.

Constant education on available tools and data assets and sharing big data assets throughout the organization are as the two main differentiators between successful cloud adoption and abandonment, according to Rodatus. “The successful customers we work with … see adoption. It spreads throughout the organization, it has increasing momentum and adoption across various business departments from many high-value use cases,” he said.

The future is clear for Rodatus: “You see these hybrid, very agile services emerging throughout our customer base, and I believe this will be the future,” he concluded.

Watch Burris and Rodatus discuss trends in big data analytics in-depth below, and be sure to check out more of SiliconANGLE’s and theCUBE’s CUBE Conversations. (* Disclosure: Datameer Inc. sponsored this segment of theCUBE. Neither Datameer nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE