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When working with CSV, JSON, and Parquet data types in Snowflake, how does selecting the appropriate data format impact query performance and storage efficiency?
When conducting diagnostic analysis, why is it essential to collect related data and demographics?
How do aggregate functions differ from window functions in Snowflake?
Which aspects are important when making predictions based on data for forecasting purposes? (Select all that apply)
How does leveraging partition pruning optimize query performance in Snowflake?
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