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Every data project starts with messy, incomplete data — and that's exactly where the interesting work begins. In this post, I walk through the five-step framework I use to move from raw CSV files to clear, actionable insights.

Despite the rise of Python libraries and BI tools, SQL remains the most versatile language for querying and transforming large datasets efficiently. Here's why every data professional should master it first.