1 - It is basically used to filter the data from redundancies
2 - helps to identify the faulty points in the data -> if identified then can easily be removed or fixed
1 - Understand the data: understanding variables, rows, columns, data types etc
2 - Clean the data: removing unncessary features or columns, removing outliers/noise from the data
3 - Analysis of the relationship between the variables