How to determine the time complexity of an algorithm and why is it necessary?

The time complexity of an algorithm shows how the execution time changes depending on the size of the input data. It is usually expressed using the "O" notation (Big O), for example, O(n), O(n²), where n is the size of the input.

To determine the time complexity, one must analyze the number of basic operations (such as comparisons, assignments) depending on the size of the input data. For example, if there is a loop that iterates over all elements of an array of n elements, then the time complexity will be O(n).

This is important to evaluate the efficiency of the algorithm and understand how it will perform on large data, as well as to choose the optimal algorithm for the task.