Design Data Ingestion and Transformation Pipelines ARA-C01 Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Which Snowflake feature can be used to encapsulate a series of transformation steps as a reusable procedural logic block?

   • AExternal function
   • BView
   • CStream
   • DStored procedure
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2. 7foundation · easy

   Which Snowflake feature is commonly used in streaming ingestion pipelines to load data from Kafka topics into Snowflake tables?

   • AStored procedure with event-driven trigger
   • BSnowpipe with Kafka connector
   • CCOPY INTO with scheduled task
   • DExternal table with auto-refresh
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4. 8foundation · easy

   What is a recommended practice for handling errors in a data pipeline to ensure reliable data delivery?

   • ASend all errors to an external system automatically
   • BStop the pipeline at the first error
   • CLog errors and continue processing
   • DIgnore errors to avoid disruption
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5. 9application · medium

   A bank loads transaction data from multiple source systems into a staging table. Each source has a different file format, and the team has observed that some files contain duplicate transaction IDs and some have missing required fields. The pipeline must reject invalid files, log the errors, and only load valid data into the final table. Which design should the architect implement?

   • AUse COPY INTO with the ON_ERROR option set to 'CONTINUE' and then run a SQL query to identify and remove duplicates before loading into the final table.
   • BUse a Snowflake task to run a SELECT statement that checks for duplicates and missing fields, and if any are found, abort the entire pipeline.
   • CLoad all files into a staging table, then use a stored procedure to validate the data, log errors to a separate table, and insert only valid rows into the final table.
   • DConfigure the COPY INTO command with the VALIDATION_MODE parameter set to 'RETURN_ERRORS' and manually review the output before loading.
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6. 10foundation · easy

   Which Snowflake feature allows you to mask sensitive data in a column based on the role of the user querying the data?

   • ARow-level security
   • BAccess control lists
   • CDynamic data masking
   • DEncryption
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