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In this short paper, we’ll look at what constitutes an “unmanaged” device, approaches to discovery, and how continuous data aggregation and correlation helps automate unmanaged device discovery.
Cohesity DataPlatform Virtual Edition™ is a software-defined platform that consolidates secondary data and applications on a single virtual appliance to overcome mass data fragmentation.
By leveraging Cohesity’s industry-leading solutions and platforms, Tech Data can help channel partners capitalize on digital transformation and increase their revenue through Tech Data’s extensive knowledge and technical expertise around Cohesity technologies and products.
Cohesity Imanis Data is a high-performance, software-defined, backup, recovery, and data management solution for a wide range of leading Hadoop Distributed File Systems and NoSQL distributed databases including MongoDB, Cassandra, CouchbaseDB, and Hbase, running on-premises, in the public cloud or both.
Achieve the goal of a secure data lake in the cloud, with elastic scale and consistent security policies through Cloudera's Shared Data Experience on CDP.
With shrinking IT budgets and increased Congressional oversight, the U.S. Department of the Navy (DON) is leading the way by implementing category management and strategic sourcing to ensure the Warfighter is buying smarter and more like a single enterprise.
Modernize cloud analytics quickly and cost-effectively with intelligent, automated cloud lakehouse data management from Informatica.
Cohesity DataPlatformTM consolidates data and applications including backups, files, objects, dev/test, and analytics on a single, software-defined platform.
During this podcast episode you’ll hear about why DLT picked Red Hat to be a significant technology provider for the Secure Software Factory. Hear how Red Hat is providing leading / innovative technologies and their views on next generation workloads, how they’re future proofing agencies environments and securing hybrid clouds, and more.
As a partner of a government-funded health and science consortium, a large university was looking for a cost-effective, scalable, and secure platform to host their scientific study data and application.
Get the most from Computer Vision and AI with a shared services model.
Enterprises need to be confident in their ability to reduce security risk and achieve business agility without sacrificing one for the other.
Detecting and protecting from threats requires systems and analysts to proactively and reactively analyze large volumes of data. The volume and speed of the data coming in prevents users from performing even the most basic security analysis for much of the data. Deploying systems to store, organize, and analyze the data is a lengthy and expensive process.
While moving to cloud services, businesses find challenges such as: limited visibility, changing business demands and hackneyed cloud provisioning, to name a few. How do you reduce security risk when the game keeps changing?
Good APIs are hard to come by and inefficient coding has far reaching implications. DevOps teams working to spin up and integrate newer applications will find it difficult to understand and interact with poorly written APIs, and they might need to write additional, more complex code in order to use them.