Hewlett Packard Enterprise Wednesday dramatically expanded its artificial intelligence-machine learning (AI/ML) market reach with a standalone release of its Ezmeral Data Fabric. The new standalone Ezmeral edge-to-cloud data fabric brings the fast growing cloud native AI/ML platform to a new multibillion-dollar market where the data fabric offering can be used in multiple enterprise big data buildouts on its own. HPE made the decision to establish a separate standalone version of the data fabric in direct response to customers, said HPE Chief Technology Officer and Head of Software Kumar Sreekanti (pictured above). "It's a huge market opportunity," he said. "Customers have asked for this because it is a very proven platform with phenomenal scale. Many customers want to first deploy the data platform and later on bring in the Ezmeral container platform."

Less than 10% … that's how many artificial-intelligence test projects are estimated to be deployed into full-scale production in enterprise environments, according to a recent report from the International Institute for Analytics. There are a number of reasons for this surprisingly small amount, including an overwhelming amount of data and the lack of easy-to-use tools to analyze it. It's a problem that calls for operationalizing AI and machine learning, making it accessible and repeatable consistently. "Ultimately, if you want to get business value from those models and all of the hard work that you've done, it has to be injected into the business process," said Anant Chintamaneni (pictured), vice president and general manager of BlueData at Hewlett Packard Enterprise Co. "Operationalization of machine learning is ultimately the key, and that's the progression that enterprises have to make." Burris was joined for a digital community event by co-host Stu Miniman (@stu), and they also interviewed Nanda Vijaydev, distinguished technologist and lead data scientist at HPE; Patrick Osborne, vice president and general manager of big data, analytics, and scale-out data platforms at HPE; and Wikibon analyst James Kobielus (@jameskobielus).