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.
