An Architect needs to automate the daily Import of two files from an external stage into Snowflake. One file has Parquet-formatted data, the other has CSV-formatted data. How should the data be joined

Question

Options

• AUse Snowpipe to ingest the two files, then create a materialized view to produce the final result
• BCreate a task using Snowflake scripting that will import the files, and then call a User-Defined
• CCreate a JavaScript stored procedure to read. join, and aggregate the data directly from the
• DCreate a materialized view to read, Join, and aggregate the data directly from the external stage,

• A
  4% (2)
• B
  85% (39)
• C
  9% (4)
• D
  2% (1)

Explanation

To automate a daily import of two files (Parquet and CSV) from an external stage and join/aggregate the results, a Snowflake Task using Snowflake Scripting is the correct approach (Option B). Tasks support scheduling (e.g., CRON-based daily triggers) and Snowflake Scripting provides imperative control to orchestrate the COPY INTO operations for both file formats sequentially, then call a User-Defined Table Function (UDTF) or stored procedure to join and aggregate the data. Option A is incorrect because Snowpipe is designed for continuous micro-batch ingestion, not scheduled batch imports, and materialized views cannot source from external stages. Option D is incorrect because materialized views cannot be defined on external stages. Option C (JavaScript stored procedure) can work but is less ideal than native Snowflake Scripting with Tasks for this orchestration pattern.

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