Exam DEA-C02 Topic 1 Question 324 Discussion

Actual exam question for Snowflake's DEA-C02 exam
Question #: 324
Topic #: 1

You are tasked with designing a data pipeline to load data from an Azure Blob Storage container into Snowflake using an external stage. The data is in CSV format, compressed using GZIP. The container contains millions of small CSV files. To optimize the data loading process and minimize cost, which of the following strategies would you implement, considering both stage configuration and COPY INTO options? Choose TWO that apply.

A. Use the 'VALIDATION MODE = RETURN ERRORS option in the 'COPY INTO' statement to identify and correct any data quality issues during the load. This ensures that only clean data is loaded into Snowflake. B. Create a pipe object with 'AUTO INGEST = TRUE to automatically ingest new files as they are added to the Azure Blob Storage container. This ensures near real-time data ingestion. C. Leverage Snowflake's Snowpipe with a REST API endpoint to trigger data loads whenever new files are available in the Azure Blob Storage container. D. Use the 'MATCH BY COLUMN NAME = CASE INSENSITIVE option with a copy transformation in the 'COPY INTO' statement to ensure that the column order in the CSV files doesn't affect the data load. E. Consolidate the small CSV files in the Azure Blob Storage container into larger files before loading them into Snowflake. This reduces the overhead of processing numerous small files.

Suggested Answer: C,E Vote an answer

Consolidating small files into larger files (option E) significantly improves COPY INTO performance by reducing overhead. Using Snowpipe with a REST API endpoint (option C) allows for efficient, triggered data loading. 'VALIDATION MODE (option A) is useful for data quality but doesn't directly address optimization for millions of small files. 'AUTO INGEST (option B) is specific to AWS S3 and Google Cloud Storage, not Azure Blob Storage event notifications. Column matching (option D) addresses schema flexibility, not optimization.

by Meredith at Oct 23, 2025, 03:21 AM

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