Snowflake Exam DSA-C02 Topic 4 Question 34 Discussion

Actual exam question for Snowflake's DSA-C02 exam

Question #: 34
Topic #: 4

Data Scientist used streams in ELT (extract, load, transform) processes where new data inserted in-to a staging table is tracked by a stream. A set of SQL statements transform and insert the stream contents into a set of production tables. Raw data is coming in the JSON format, but for analysis he needs to transform it into relational columns in the production tables. which of the following Data transformation SQL function he can used to achieve the same?

AHe could not apply Transformation on Stream table data.

Blateral flatten()

CMETADATA$ACTION ()

DTranspose()

Show Suggested Answer

Suggested Answer: B

To know about lateral flatten SQL Function, please refer:

https://docs.snowflake.com/en/sql-reference/constructs/join-lateral#example-of-using-lateral-with-flatten

by Caren at Nov 14, 2024, 09:42 PM

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James

1 days ago

I agree with Cory, lateral flatten() function is commonly used for this type of transformation.

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Cory

14 days ago

I think the Data Scientist can use lateral flatten() function for transforming the JSON data into relational columns.

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Emiko

24 days ago

Hold up, option A? Really? You can't apply transformations on stream data? That's just nonsense!

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Erinn

26 days ago

Hmm, I'd go with option B. Lateral flatten() seems like the perfect SQL function to transform that JSON data into relational columns.

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Gretchen

11 days ago

I think METADATA$ACTION () might also work for this transformation.

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Kirk

14 days ago

I agree, lateral flatten() is the way to go for transforming JSON data.

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