### Q1: What is one simple technique to handle missing values in a financial dataset?  
### Q2: How would you apply imputation to fill in missing transaction values, and what are some common methods used?  
### Q3: What are the advanced methods for predicting missing values based on other available features in a dataset?  
### Q4: What is the importance of identifying outliers in transaction data, and what method can be used to do so?  
### Q5: Describe a moderate approach to handling outliers once they have been identified in your dataset.  
### Q6: What are the implications of not addressing outliers in financial data analysis?  
### Q7: Why is it critical to apply normalization when preparing financial datasets for analysis?  
### Q8: How does standardization differ from normalization in data transformation techniques, and why might one be preferred over the other?  
### Q9: What challenges might arise when encoding categorical variables in finance, and how can these be effectively addressed?