DAA-C01 Exam Dumps | A data analyst is using a data feed from the Snowflake Marketplace which delivers data in JSON format.

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Question 117/151

A data analyst is using a data feed from the Snowflake Marketplace which delivers data in JSON format. They need to create a relational table to store this data, but the JSON structure is deeply nested and contains arrays. Which of the following approaches would be the MOST efficient way to create the table and load the JSON data, taking into consideration performance and minimizing data duplication?
(Choose two)

A. Create a single table with a VARIANT column to store the entire JSON document.

B. Create multiple relational tables, flattening the JSON structure using LATERAL FLATTEN and storing related data in separate tables.

C. Use a stored procedure to parse the JSON data and insert it into a pre-defined relational table.

D. Create a view on top of the JSON data stored in a single VARIANT column, using JSON path expressions to extract specific fields.

E. Load the JSON data into a staging table, then use a series of INSERT statements with JSON parsing functions to populate the final relational table.

Correct Answer: B,E

Options B and E are the most efficient. Option B: Using 'LATERAL FLATTEN' allows you to break down the JSON structure into relational tables, minimizing data duplication and improving query performance for specific fields. Option E: Loading the JSON data into a staging table and then using INSERT statements with JSON parsing functions provides a controlled and efficient way to transform and load the data into the final relational table. Option A: While storing the entire JSON in a VARIANT column is easy, it can lead to performance issues for queries that need to access specific fields within the JSON. Option C: Stored procedures can be complex and less efficient than using native Snowflake JSON parsing functions. Option D: Creating views on VARIANT columns can still suffer from performance issues compared to flattened relational tables.

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