What is data cleansing?

Data Science, AI and ML
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What is data cleansing?

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Data Cleansing is basically a method of cleaning the data means how efficiently we can prepare the data before using in the model for prediction.
It basically requires to fill the missing values using mean,median,mode and delete the unnecessary part of the data using feature engineering techniques.

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Data cleaning is the process of preparing data for analysis by removing or modifying data that is incorrect, incomplete, irrelevant, duplicated, or improperly formatted. This data is usually not necessary or helpful when it comes to analyzing data because it may hinder the process or provide inaccurate results.

Data Cleaning (or cleansing) is the work of detecting and correcting violations of data quality business rules.