• Handling large and complex
  datasets
• Data quality and cleaning
• Choosing appropriate visual
  representations
• Handling real-time and streaming
  data
• Interactivity and user engagement
• Design and aesthetics
• Accessibility and inclusivity
• Insufficient flexibility

Addressing these challenges requires a
combination of technical skills, domain expertise,
and an iterative design process. It is important to
understand the specific requirements of the data
and the intended audience to develop effective
data visualizations that convey insights accurately
and facilitate data exploration and understanding.

• Data storage and management
• Data preprocessing and cleaning
• Scalability and performance
• Complex data structures and
  formats
• Privacy and security
• Real-time and streaming data
  analysis
• Machine learning at scale