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Data preprocessing is a fundamental step in data warehousing and data mining because the quality of mining results depends directly on the quality of the input data. A financial institution often collects customer information from multiple sources such as bank branches, online banking platforms, mobile applications, credit card systems, insurance records, and loan management systems. Such data frequently contains noise, missing values, inconsistencies, duplicates, and redundant attributes. Before applying mining algorithms for fraud detection, customer segmentation, credit risk analysis, or loan approval, appropriate preprocessing techniques must be applied. Data cleaning is the first and most important preprocessing step. _____ ________ _________ ____ ____ _________ ____ ________ ________ _________ __________.
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