This question evaluates skills in data normalization, weighted aggregation, and scalable data processing for deriving the most popular city from inconsistent vote records.
Given a set of concert venue vote records, determine which city is the most popular. How would you normalize city names that have multiple spellings (e.g., 'NYC', 'New York')? If votes carry different weights, how would you incorporate them? Describe how you would scale the solution for large datasets.