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You are using an Azure Synapse Analytics serverless SQL pool to query a collection of Apache Parquet files by using automatic schema inference. The files contain more than 40 million rows of UTF-8-encoded business names, survey names, and participant counts. The database is configured to use the default collation.
The queries use open row set and infer the schema shown in the following table.

You need to recommend changes to the queries to reduce I/O reads and tempdb usage.
Solution: You recommend defining a data source and view for the Parquet files. You recommend updating the query to use the view.
Does this meet the goal?