Big O notation is a way to analyze the efficiency of algorithms by describing how their runtime or space requirements grow as the input size increases. It is crucial for designing and optimizing algorithms to ensure they perform well with large datasets, helping developers make informed decisions about which algorithm to use in different scenarios.

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