### Q1: What is the primary purpose of data cleaning in data analysis?  
### Q2: How can you handle missing values in your dataset according to the techniques discussed in the lesson?  
### Q3: What are some advanced tools for cleaning data mentioned in the content that require programming knowledge?  
### Q4: In what ways can clean data enhance the credibility of your reports?  
### Q5: Which technique for data preparation would you prioritize for ensuring data uniqueness in your analysis?  
### Q6: How do normalization techniques help in comparing different data points?  
### Q7: What communication strategies can you use to explain the importance of data cleaning to stakeholders?  
### Q8: How would you convey the benefits of using tools like OpenRefine to a team unfamiliar with data cleaning?  
### Q9: What approach would you take to facilitate a discussion on improving data preparation processes within your organization?