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SQL problems involving ranking, window functions, and relational joins are commonly asked in data engineering and analytics interviews at large tech companies. Market Analysis II reflects the type of analytical query logic often tested.
The optimal approach uses SQL window functions such as ROW_NUMBER() to rank each seller’s orders by date. After identifying the second sale, you join with item and user tables to compare the item's brand with the seller's favorite brand.
Key SQL concepts include window functions, especially ROW_NUMBER(), along with JOIN operations and conditional logic. These tools help isolate the second order per seller and compare brand values efficiently.
Window functions are the most suitable feature for this problem because they allow ranking rows within partitions. This makes it easy to identify the second item sold by each seller without complex subqueries.