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A company has built a data pipeline using Snowpipe to ingest files from an Amazon...

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A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.

The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.

What step can be taken to improve the pruning of the reporting tables?

A.

Eliminate the use of Snowpipe and load the files into internal stages using PUT commands.

B.

Increase the size of the virtual warehouse to a size 5X-Large.

C.

Use an ORDER BY command to load the reporting tables.

D.

Create larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.

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