Mastering Data Cleaning & Data Preprocessing

To get the best results from data analysis or machine learning, your data must be clean and well-prepared. Data cleaning means fixing or removing errors, duplicates, and missing information. Preprocessing makes the data easier to use by transforming it—like scaling numbers, encoding categories, or formatting text. These steps ensure your data is accurate and consistent, which is key to getting meaningful results. Without clean data, even the most advanced tools and algorithms can fail. Think of it like preparing clean ingredients before cooking—the better the prep, the better the outcome.