Resiliency
Resiliency in Data Science refers to the ability of a system to recover from failures and continue to function. It involves designing systems that can withstand unexpected events, such as hardware failures, network outages, or cyber attacks, and can quickly recover from them without losing data or compromising the integrity of the system. Resiliency is achieved through redundancy, fault tolerance, and disaster recovery planning. Redundancy involves having multiple copies of data or systems in different locations, so that if one fails, the others can take over. Fault tolerance involves designing systems that can continue to function even if some components fail. Disaster recovery planning involves having a plan in place to quickly restore systems and data in the event of a major outage or disaster.
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