A marketing manager wants last month's West region sales with discounts above 15%. Which decision is the best method to display those results without added overhead?
Assemble a pivot for every monthly discount in the West, then discard data that is outside the discount requirement
Migrate the database schema, apply region and discount limitations afterward
Merge all recent sales from every region, then remove the other regions and discounts that do not qualify
Capture matching entries based on discount, region, and date parameters during the data retrieval process
Capturing the relevant entries using region, timeframe, and discount parameters focuses on the requested set. Large-scale migrations, full data loads, or pivoting everything first can consume more resources and do not emphasize retrieving fewer rows from the source.
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Why is capturing relevant entries during data retrieval more efficient than filtering afterward?
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What are parameters in a database query, and how do they work?
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What is the risk of using a pivot table or data aggregation if the dataset is too large?