What is data clearing in data mining? Elaborate with an example.

Data cleaning (clearing) is fixing errors in raw data before mining — garbage in, garbage out. Steps: remove duplicates, fill/correct missing values, fix formats, drop outliers.

Example: Citizen survey has Age: 250, blank phone, Kathmandu/KTM/ktm spellings, duplicate citizenship 123. Cleaning: delete duplicate, set 250 → flag for verification, standardize to Kathmandu, fill missing phone with "N/A" or revisit. Only then can mining find true patterns like "most service seekers aged 25–40".