Dear Ankur Taya

There are many methods for data preprocessing but most of them falls in to these categories :

• Dimensionality Reduction
• Data Cleaning
• Feature Engineering ( Feature Extraction )
• Sampling Data
• Data Transformation ( Normalization, Standardization, etc )
• Imbalanced Data

See these links for more information:

1 - https://www.geeksforgeeks.org/data-preprocessing-in-data-mining/

2 - https://www.scalablepath.com/data-science/data-preprocessing-phase

For your second question nowadays it is very common that researchers using forecasting methods ( mostly Machine Learning methods ) to produce new data same as missed data .