Data may be driving today's enterprise, but the engine is only using a fraction of its horsepower. A recent information technology study by Cohesity Inc. found that a significant majority -- approximately 80 percent -- of an organization's data is not mission critical. It's languishing in backups, object stores and archives scattered across public and private clouds. The result is data fragmentation, a growing issue within the IT community that involves the spread of information into infrastructure silos, preventing a business from realizing the true value of the data it owns. "We've always had data fragmentation, but it's becoming worse," said Zeus Kerravala (pictured, left), founder and principal analyst at ZK Research, a division of Kerravala Consulting Inc. "It's hampering a company's ability to make critical decisions to be able to move fast and keep up with a lot of cloud-native counterparts. If they don't get a handle on this, they're going to fall further and further behind."

Organisations are starting to realise that leveraging artificial intelligence and machine learning, as a business tool, is important for success. Increasingly, organisations are looking to automate data management operations, via AI and machine learning. Artificial intelligence-led tools are now helping business know their customers like never before. "Put into the context of a specific use-case, one of the challenges in data management is determining optimal RPO and RTO to support the business and then ensuring that these business requirements are met," explains Mankude. "This is where an enterprise data management platform can gather sufficient information from the backups and restores that have been occurring, and feed this into an AI engine to predict the RPO and RTO of a workflow," he continues.

WIRE)--Imanis Data, the leader in enterprise data management powered by machine learning, today announced a major upgrade to the Imanis Data Management Platform, continuing the company's momentum since raising $13.5 million Series B funding earlier this year. The new Version 4.0 includes multiple industry firsts including autonomous backup, any-point-in-time recovery for multiple NoSQL databases, enhanced ransomware prevention, as well as numerous Imanis Data management enhancements. Hadoop and NoSQL applications are running in virtually every enterprise on-premises and in the cloud, but they lack enterprise data management capabilities, exposing organizations to data loss, downtime, and cyberattacks. "According to our research, 78% of organizations currently use NoSQL databases and an additional 18% plan to in the future," said Christophe Bertrand, senior analyst for data protection, at ESG Research. "The data protection market in this space is underserved by traditional vendors and Imanis Data with their unique machine learning approach is setting the bar for Hadoop and NoSQL enterprise data management."