This vendor-written tech primer has been edited to eliminate product promotion, but readers should note it will likely favor the submitter’s approach.
Data is the DNA of the modern organization and found in the cloud, behind four walls and at the network’s edge. Data is also growing at a greater speed than ever before. This unique combination of growing data complexity, sprawl and volume is forcing IT to rethink traditional approaches to backup and recovery.
No longer can organizations afford to approach such practices without substantial insight into both how they are approaching these operations (load, clients, resources, service levels) and insight into the information itself. Now more than ever, analytics is necessary to ensure business resiliency.
There are four primary types of analysis that can be applied to backup and recovery: environmental, retrospective, predictive, and prescriptive analysis. Each provides a window into the overall network. And when combined, they allow enterprises to be proactive in prioritizing data, predicting resource utilization, mitigating risk and optimizing infrastructure in order to reduce the burden on resources and manage the costs. This combination delivers on the promise of “backup with brains.”
Today’s backup and recovery responsibility has to extend beyond the traditional four walls of the corporate headquarters to support emerging cloud, mobile and virtual platforms. As such, organizations are faced with needing to better understand the data, where it is located and the value that it provides to the organization. The understanding environmental analysis delivers allows IT to define how it is going to manage, backup and deliver the information in a transparent manner that supports its overall business objectives.
Retrospective analytics allow teams to gain insight into the health and success of the backup process, resource utilization, as well as areas of optimization. Having deep knowledge of past backup process and infrastructure utilization can ensure that the most critical applications gain access and priority to the resources needed to complete backups on time, and non-disruptively.
This form of analysis requires greater insight into information – what type of data it is and the relative importance it has to the organization. With this added insight, organizations are able to automatically classify their data, define what is being held, determine if it is critical to the business and set guidelines in terms of how and when it is backed up. IT executives are increasingly leveraging this form of analytics to recommend how to best optimize the backup system to take advantage of additional resource and capacity – to improve not only the protection of the data but also the long-term retention for compliance.
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