Blog Archives

Three Steps to Moving Legacy Backups to the Cloud

One of the significant challenges regarding data protection is managing its data set. Secondary storage tiers store five to ten times as much data as production data stores and can overwhelm the data center. IT planners are looking to cloud

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The State of Disaster Recovery Planning

Disaster Recovery Plans (DRP) are supposed to be an organization’s playbook if they need to recover critical data center operations after a disaster. The issue is that in most organizations, the DRP is outdated if it exists at all. Disaster

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Fixing the Broken Archive – Archive360 2018 Update

Data Management (archiving) looks good on the IT whiteboard. It is the process of moving old data from existing primary storage systems to an archive system. The process should free up primary storage capacity, simplify the data protection process and

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Posted in Briefing Note

Webinar: How to Create a Great Disaster Recovery Plan

Many studies indicate that organizations have a shallow confidence level in their ability to recover from a disaster. The disaster recovery plan is often an ad-hoc plan that requires IT to scramble when disaster strikes. If the recovery effort succeeds,

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Why Multi-Vendor Storage Happens and How to Manage It

When core IT receives a new workload, application owners tell IT what storage resources the workload needs as it enters production and what the expected resources are when it matures. Core IT then has to look at its available storage

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Can Data Management be Done Better in the Cloud?

Backup, archive and managing secondary storage capacities are a constant thorn in IT’s side. Backup is often a disaggregated mess, and IT doesn’t have time to implement archiving. Secondary storage capacities, thanks to initiatives like IoT and next-generation applications, threaten

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AI Needs an NVMe-Optimized File System

Analytics is evolving from big data, machine learning to artificial intelligence. Machine learning is the analysis of data at rest, artificial intelligence (AI) is the analysis of data in real-time. Machine learning is predictive; AI is cognitive. The requirements of

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How to Leverage the Cloud for Unstructured Data Protection

Unstructured data is growing at alarming rates. The growth is the result of not only increased user activity but also by machines and IoT devices. Re-creation of this data isn’t possible. It is a point time capture of sensory data.

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The Importance of Consolidation for Secure Storage

The Security Problems with Multi-Vendor Data Storage One of the most common data center trends is storage system sprawl. In today’s data center, every environment or workload has a unique storage architecture. While dispersed storage does allow IT to target

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Dealing with the AI and Analytics Data Explosion – MapR Briefing Note

Accuracy and response time defines the success or failure of an AI or analytics project. The faster and more accurate the response the more trusted the system is. The more data provided to the project the more accurate it becomes.

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Posted in Briefing Note