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Data resiliency

Data resiliency

Data resiliency definition

Data resiliency refers to a company’s readiness to quickly recover data access and functionality after significant events such as hardware failure or even a cybersecurity incident. Implementing a data resilience plan involves outlining potential threats, finding ways to minimize data loss, and ensuring the continuity of data operations.

See also: data backup, data breach

Key elements of data resiliency

  • Backup. It’s a primary way to ensure data can be restored from a copy. However, how often you need to back up data, how long you need to store it, and whether you should store data on a cloud or not, depends largely on the company’s needs. Not to mention that backups must also be protected from physical damage and cyber threats.
  • Replication. It helps maintain real-time or near-real-time copies of data in separate locations. Replication can be synchronous and asynchronous, while its speed depends on various factors such as physical distance.
  • Failover. Failover mechanisms automatically switch operations to a secondary system or location when the primary system is compromised, ensuring continued data accessibility.
  • Fault tolerance. It enables systems to operate seamlessly even in the face of failures, offering a continuous user experience. But fault tolerance can also be costly as you may need multiple sets of hardware.
  • Data protection. Strong encryption, firewalls, intrusion detection systems, and access control can help protect data from unauthorized access, data breaches, corruption, and theft.
  • Disaster recovery planning. Creating a plan and testing it helps prepare for potential disruptions, ensuring an efficient data recovery.

Further reading

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