### Q1: What are some key reasons for the importance of clean data in financial decision-making?  
### Q2: How can low-code tools improve data management practices in businesses?  
### Q3: What specific challenges might arise when assessing data quality and its impact on AI outcomes?  
### Q4: In what ways can businesses leverage clean data for better financial outcomes?  
### Q5: How might a mixed approach to coding enhance the understanding of data management best practices?  
### Q6: What are the potential consequences of poor data quality on AI-driven decision-making?  
### Q7: How can effective communication skills help in presenting the importance of data quality to a non-technical audience?  
### Q8: What strategies can be employed to communicate data management best practices within a team?  
### Q9: How can improving communication around data issues foster a culture of accountability in a business environment?