Welcome back to our course on algorithmic problem-solving with JavaScript data structures. Today, we sharpen our focus on Maps—a powerful data structure you're already familiar with from our prior discussions. This lesson will demonstrate how we can leverage Maps to efficiently solve common algorithmic problems you might face in a coding interview.

Let's put it in a familiar scenario: at a party, it's easy to notice that one person everyone seems to know. This person, akin to the "celebrity" at the party, serves as the analogy for an element in an array that appears more than half the time — our task is to identify this celebrity element amid a crowd of numbers.

The naive way to identify this celebrity is to count the occurrences of each number by looping over the array for each element and seeing if it repeats sufficiently to be our star. Computationally, this translates to significant time (quadratic time complexity) for larger arrays — an apparent inefficiency.

Now, let's be savvy about this. Enter the Map: your sophisticated voting tally system. With it, you can keep a running total of each element appearance as you go through the array once rather than reviewing the entire list for each integer.

Let's dissect the process in our finding celebrity analogy step by step:

Here, we're preparing our Map for counts and establishing the majority threshold — the number of people who know you need to win the celebrity prize.