DEA-C02 Exam Dumps | You are tasked with loading a large dataset (50TB) of JSON files into Snowflake. The JSON files are complex,

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Question 43/149

You are tasked with loading a large dataset (50TB) of JSON files into Snowflake. The JSON files are complex, deeply nested, and irregularly structured. You want to maximize loading performance while minimizing storage costs and ensuring data integrity. You have a dedicated Snowflake virtual warehouse (X-Large).
Which combination of approaches would be MOST effective?

A. Use Snowpipe with auto-ingest, create a single VARIANT column in your target table, and rely solely on Snowflake's automatic schema detection.

B. Pre-process the JSON data using a Python script with Pandas to flatten the structure and convert it into a relational format like CSV. Then, load the CSV files using the COPY INTO command with gzip compression.

C. Use Snowpipe with auto-ingest, create a raw VARIANT column alongside projected relational columns for frequently accessed fields, and use search optimization on those projected columns.

D. Load the JSON data using the COPY INTO command with no pre-processing. Create a VIEW on top of the raw VARIANT column to flatten the data for querying.

E. Load the JSON data using the COPY INTO command with gzip compression. Create a raw VARIANT column alongside projected relational columns for frequently accessed fields, and use materialized views to improve query performance.

Correct Answer: C

Option C is the most effective. Snowpipe provides continuous loading. A raw VARIANT column captures all data, and projecting commonly accessed fields into relational columns optimizes query performance. Search optimization on the projected columns allows for faster filtering and lookups. Options A, B, D, and E have trade-offs. A lacks optimized querying and can lead to expensive computations on the variant column. B requires pre-processing and may lose data fidelity. D impacts query performance due to runtime flattening. E introduces complexities with materialized view maintenance.

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