What are the different steps involved in data preprocessing?

Data preprocessing is an essential step in data analysis and involves several stages. The first step is data cleaning, which includes removing any irrelevant or duplicate data points, handling missing values, and correcting inconsistent entries. The next step is data transformation, where features are converted or normalized to meet specific requirements, such as scaling numerical variables or encoding categorical variables. Feature selection is then carried out to identify the most relevant features for analysis, removing redundant or insignificant ones. The final step is data integration, where multiple datasets are combined, and data reduction techniques may be applied to reduce dimensionality. Overall, these steps ensure that the data is clean, consistent, and suitable for further analysis.

This mind map was published on 27 September 2023 and has been viewed 117 times.