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Veeam Software
Raymond Goh, Head of Systems Engineering, Asia & Japan
Intelligent Data Management in the Era of Virtualization


Raymond Goh
The virtualization process is achieved through hypervisor software which is able to control the amount of access various operating systems (OS) have with the hardware resources. Organizations are able to partition a physical server into several virtual machines (VM), allowing for multiple OS to run while sharing the resources of a single physical computer.
The VM is completely mobile and can be effortlessly moved from one physical server to another, to a data center or even to a thumb drive. Users no longer require purchasing computers or hardware to run additional OS. The portability of such resources allows for multiple benefits. Employees are given access to the same working environment effortlessly, without missing out on specific software packages or IT settings. In the same manner, organizations can leverage these functions to shift around workloads as required—whether that is on-premises, in the hyper-public cloud, through a service provider, or an outright transition to a Software as a Service model—enabling more efficient processes.
However, it is imperative for organizations to understand that increased agility of data means that they now have the responsibility to better manage and protect it. Today’s data differs from yesterday’s data. Every process, whether an external client interaction or internal employee task, leaves a trail of data.
The growth of data has been and will continue to be incredible. Human and machine-generated data is growing ten times faster than traditional business data, and machine data is growing at 50 times that of traditional business data. Enterprises need to learn how to intelligently manage these vast amounts of data that can be analyzed and gleaned for insights.
Another crucial component of data management
for organizations is to ensure it is always available for consumers. The modern customer demands efficient and seamless service. They want digital transactions to always work as expected, and enterprises need to meet these demands to build confidence and trust. Hyper-Availability of data is the new expectation for both consumers and enterprises. The current state of availability for organizations is one in which data is manually relocated to optimize cost. While this method might be working now, the future of availability follows a more autonomous model where the system can self-direct and respond to significant changes in data across the enterprise.
For those looking to meet the expectations and future demands of Hyper-Availability, there are five stages of intelligent data management that businesses can follow— Backup, Aggregation, Visibility, Orchestration and Automation.
Backup
The first step in achieving the Hyper-Availability required for the future is to back up all workloads and ensure they are always recoverable in the event of outages, attack or theft.
Aggregation
Enterprises should ensure an aggregated view of service level compliance for protection and availability of data across multi-cloud environments.
Visibility
To improve management of data, unified visibility and control into usage, performance issues and operations are pertinent.
Orchestration
The next stage is orchestration, where organizations can seamlessly move data around to ensure business continuity, compliance, security and optimal use of resources.
Automation
When businesses successfully achieve and implement these four steps, data management becomes automated. Data grows to be self-managing, learning to back itself up, migrating to ideal locations based on business needs, and securing itself during anomalous activity for instantaneous recovery.
The growth of data is not stopping anytime soon, and the journey to reach Hyper-Availability is not one that can be completed in a single day. However, forward-thinking business leaders can turn this challenge into an opportunity.
Check Out: Top Master Data Management Solutions
Another crucial component of data management
for organizations is to ensure it is always available for consumers. The modern customer demands efficient and seamless service. They want digital transactions to always work as expected, and enterprises need to meet these demands to build confidence and trust. Hyper-Availability of data is the new expectation for both consumers and enterprises. The current state of availability for organizations is one in which data is manually relocated to optimize cost. While this method might be working now, the future of availability follows a more autonomous model where the system can self-direct and respond to significant changes in data across the enterprise.
For those looking to meet the expectations and future demands of Hyper-Availability, there are five stages of intelligent data management that businesses can follow— Backup, Aggregation, Visibility, Orchestration and Automation.
Backup
The first step in achieving the Hyper-Availability required for the future is to back up all workloads and ensure they are always recoverable in the event of outages, attack or theft.
Aggregation
Enterprises should ensure an aggregated view of service level compliance for protection and availability of data across multi-cloud environments.
Visibility
To improve management of data, unified visibility and control into usage, performance issues and operations are pertinent.
Orchestration
The next stage is orchestration, where organizations can seamlessly move data around to ensure business continuity, compliance, security and optimal use of resources.
Automation
When businesses successfully achieve and implement these four steps, data management becomes automated. Data grows to be self-managing, learning to back itself up, migrating to ideal locations based on business needs, and securing itself during anomalous activity for instantaneous recovery.
The growth of data is not stopping anytime soon, and the journey to reach Hyper-Availability is not one that can be completed in a single day. However, forward-thinking business leaders can turn this challenge into an opportunity.
The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.


