This project can be broken down into several parts: The first part is Data Understanding, where the data is analyzed to gain insight into its structure and content. This is followed by Data Visualization, which helps to better understand the patterns and relationships in the data. T he next step is Data Preprocessing, which involves dealing with missing values and scaling the data to prepare it for modeling. Finally, the project involves modeling using Kmeans and PCA, which is used to cluster customers based on their behavior. This approach can be useful in identifying customer groups with similar characteristics and tailoring marketing efforts to their needs