Dates and times are the backbone of almost every dataset. From analyzing sales trends to tracking project deadlines, your ability to work with temporal data is a key skill for any data professional. Yet, raw date columns can be messy and hard to analyze. Manually extracting years, months, or quarters is a tedious and error-prone process.