Machine learning is driving demand for data replication
March 10 2017
Data for the enterprise is now a currency of its own, yet many companies and institutions are still trying to navigate the moving of large volumes of data from on-premise to the cloud in an effort to capitalize on the value of data stored in many locations.
“I think longer-term the economic advantage of using cloud environments are undeniable. The cost advantages of hosting information in the cloud, the benefits that come from the scalability of those environments is far surpassing capabilities that organizations can invest in themselves or their own data centers,” said Paul Scott-Murphy, vice president of product management, big data/cloud, at WANdisco Inc.
During the Google Cloud Next event, Scott-Murphy spoke with Stu Miniman (@stu), host of theCUBE, SiliconANGLE Media’s mobile live streaming studio, at SiliconANGLE’s Palo Alto, CA, studio to discuss the trends WANdisco is seeing with its customers, as well as news from Google Cloud Next. (*Disclosure below.)
New use cases, new challenges for data
WANdisco’s enterprise and institutional customers are all facing similar problem: The availability of data and the combination of where it is stored makes it difficult to access and derive any benefits for them.
Taking advantage of cloud infrastructure requires WANdisco’s customers to think about how to make information available using both on-premise systems and the cloud environment where they can have access to services and analytics along with the ability to run workloads at scale.
As emerging technologies, such as the Internet of Things, Artificial Intelligence and machine learning are becoming commonplace for many businesses, moving enormous amounts of data around and keeping its integrity is paramount.
“The interesting thing about WANdisco’s approach to data replication is that we base it on this foundation of consistency, using a mathematically proven approach to distributed consensus to guarantee that changes made in one environment are represented in others, equally regardless of where those changes occur,” Scott-Murphy said.
Using IoT as an example of data existing outside of the cloud, Scott-Murphy explained the necessity for the type of consistency WANdisco provides to ensure customers are not receiving excess copies of information.
For AI and machine learning to reach its full potential, the dataset must grow. “The more information you have, the better they work, and the more capable they become,” he said, while also pointing out that the rapid rate of adoption and industry demand for these technologies is also increasing the urgency for more data.
In terms of identifying trends, Scott-Murphy mentioned that listening to customers and understanding what they want to do with information systems is critical — particularly, in an ever-changing IT industry where new IT systems and technologies are springing up on a daily basis.
Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of Google Cloud Next 2017. (*Disclosure: Some segments on SiliconANGLE Media’s theCUBE are sponsored. Sponsors have no editorial control over content on theCUBE or SiliconANGLE.)