cleaning algorithms

Cleaning algorithms are methods used by computers to improve data quality. They identify and correct or remove errors, duplicates, missing values, and inconsistencies in datasets. For example, they might standardize formats, fill in gaps, or flag suspicious entries. These algorithms ensure the data is accurate, reliable, and ready for analysis, helping organizations make better decisions based on clean, trustworthy information. They are essential for transforming raw, messy data into a usable and meaningful resource.