Considerations include data redundancy, normalization needs, query complexity, performance expectations, flexibility, and ease of maintenance when choosing the appropriate data structure for BI requirements.

Troubleshooting query performance often involves reviewing query history, adjusting warehouse configurations, and examining Query Profile attributes for optimization.

Result caching accelerates query execution by storing intermediate results, reducing processing time for repetitive or commonly accessed queries.

Visualizations enhance data comprehension, aiding effective analysis in business use scenarios.

Clones are beneficial in isolating and resolving data anomalies without impacting the original dataset, facilitating safe data cleaning practices.