This vendor-written tech primer has been edited by Network World 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.
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.
In today’s highly dynamic, diverse, and complex data environments, approaching backup and recovery with the same strategies that worked in the past is not only ill-advised, it can also create significant risk – to your organization or even to your career. Today, organizations need backup with brains, and analytics is the first and most critical step to meeting evolving business resiliency requirements.
Garber is VP of Marketing for Hewlett Packard Enterprise’s Information Management & Governance business unit – a division of HPE Software. In this role, he leads thought leadership, product messaging and go-to-market efforts for the organization’s data protection, file analysis, information archiving, records management, and eDiscovery offerings. For more information, please visit www.hpe.com.