### Q1: What is the purpose of data cleaning in data analytics?  
### Q2: How can you implement format checks in your data validation process?  
### Q3: What are some advanced techniques you can use to ensure data consistency across multiple datasets?  
### Q4: How can range checks improve the quality of customer data in your analysis?  
### Q5: Which data validation technique would you find most useful when dealing with customer feedback data, and why?  
### Q6: Can you describe a scenario where uniqueness checks might prevent a significant issue in data processing?  
### Q7: How would you explain the importance of data cleaning to a colleague who is new to data analytics?  
### Q8: What strategies can you use to communicate the need for data validation to stakeholders?  
### Q9: How can you effectively convey the impact of inaccurate data on decision-making during team meetings?