### Q1: What is the primary distinction between structured and unstructured data in the context of AI/ML?  
### Q2: How can you ensure the accuracy of data when collecting it for AI projects?  
### Q3: What are some advanced techniques you could use to analyze unstructured data effectively?  
### Q4: How can understanding data types enhance the effectiveness of your AI initiatives?  
### Q5: What measures can be taken to improve the completeness of data in your AI projects?  
### Q6: In what ways can implementing data governance enhance the overall quality of your AI data?  
### Q7: How can you effectively communicate the importance of data quality to your team?  
### Q8: What strategies would you employ to foster cross-department collaboration in data collection?  
### Q9: How can you convey the impact of data quality on AI outcomes to stakeholders in a concise manner?