andmepuhastus

Andmepuhastus, also known as data cleansing or data cleaning, is the process of detecting and correcting (or removing) corrupt or inaccurate records from a dataset. This process is crucial in data management and analysis, as it ensures the quality and reliability of the data. Data cleansing involves several steps, including data profiling, data matching, data transformation, and data validation. Data profiling involves analyzing the data to understand its structure, content, and quality. Data matching involves identifying and merging duplicate records. Data transformation involves converting data into a consistent format. Data validation involves checking the data for accuracy and completeness. Data cleansing can be performed manually or using automated tools and techniques. It is an essential step in data preparation for data analysis, data mining, and machine learning.