“processed, and transformed into a format that is suitable for analysis. This often involves removing duplicate data, correcting errors, and dealing with missing values. After data is prepared, exploratory data analysis is performed to better understand the data and identify patterns, trends, and outliers. Descriptive statistics, data visualization, and data clustering techniques are often used to explore data. Once the data is understood, statistical methods such as hypothesis testing and regression analysis can be applied to identify relationships and make predictions.”