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Backup with brains: The growing importance of analytics to business resiliency

Joe Garber, VP Marketing, Information Management & Governance, Hewlett Packard Enterprise | Jan. 4, 2016
Understanding the four types of analysis that can be applied to backup and recovery

Retrospective analytics help align organization’s three key stakeholders of backup and recovery, including the backup administrator, the infrastructure operations team and C-level executives.  It enables them to gain confidence into the organization’s ability to meet service level expectations.  Having defensible history of operational success enables enterprises to meet compliance and governance needs in their particular industry or vertical market.

Predictive analytics is growing in importance for backup and recovery.  This approach allows organizations to predict future resource needs and potential resource conflicts based on historical data patterns. Armed with this knowledge, IT team can proactively address issues before they can occur and plan for future needs such as additional capacity purchase in a proactive manner.

With predictive analytics, organizations can ease the operational demands of backup and recovery management. Enabling administrators to predict when their systems will run out of storage capacity is a great value for the team from planning perspective. Additionally, the data growth patterns can also highlight potential conflicts and resource contention that can lead to increased backup window issues. Providing knowledge about these potential future problems before it can actually occur is fairly transformational for the IT organizations.

With greater insights obtained, organizations can leverage their existing backup investment as well as plan for future capacity and infrastructure needs.  It can also serve as a critical component in the industry’s rapid movement toward automation.  Automation decreases the effort within the backup and recovery operation and ensures protection for all devices under management, by automatically applying protection policies and provisioning backup resources. This automation saves time, money, and management.

Prescriptive analytics is an emerging need for backup and recovery that enable IT leaders to get the most out of the backup gears that are already deployed, streamline key processes and improve time to remediation.

For IT operations teams responsible for managing the overall infrastructure, this form of analytics provide visual cues and steps to remediation when a problem occurs. More importantly, it creates a common vernacular between backup teams and IT operations teams during the troubleshooting process. Further, they provide visibility into the error conditions on backup jobs and issues with physical resources such as tape libraries, drives and disk systems to precisely troubleshoot what has gone wrong and how to fix it.

In summary, as organizations adjust to the reality of a changing IT world — with increasing volume, variety, and velocity of information sources, which have expanded beyond the four corporate walls — they must also expand their information management practices to keep pace with the increasing demands.  In short, they need to move from defense to offense. 

A critical first step to that end is leveraging analytics to optimize backup and recovery – to create a strategy that is just as agile as their current and future environments.  Analytics provide a snapshot into an organization’s overall data strategy.  Analytics applied to the network provide the organization with greater insight into the data that is collected, stored, and managed.  And analytics improve operational efficiencies and mitigate risk by identifying and optimizing the managed data, according to corporate information management requirements.

 

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