Snowflake COF-C02 Exam - Topic 8 Question 55 Discussion

Actual exam question for Snowflake's COF-C02 exam

Question #: 55
Topic #: 8

[All COF-C02 Questions]

When unloading data, which file format preserves the data values for floating-point number columns?

AAvro

BCSV

CJSON

DParquet

Show Suggested Answer

Suggested Answer: D

When unloading data, the Parquet file format is known for its efficiency in preserving the data values for floating-point number columns. Parquet is a columnar storage file format that offers high compression ratios and efficient data encoding schemes. It is especially effective for floating-point data, as it maintains high precision and supports efficient querying and analysis.

References:

Snowflake Documentation: Using the Parquet File Format for Unloading Data

by Audria at Apr 30, 2025, 11:21 AM

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Alona

2 months ago

I agree, Parquet handles floating-point numbers really well.

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Holley

2 months ago

Wait, so JSON doesn't preserve those values? That's surprising!

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Emogene

2 months ago

Parquet is the best for preserving floating-point values!

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Dorothy

3 months ago

Definitely Avro for schema evolution, but Parquet is solid too.

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Clorinda

3 months ago

I thought CSV was good enough for that?

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Orville

3 months ago

I’m a bit confused; I thought JSON was good for data interchange, but I guess it might not preserve floating-point values well.

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Raylene

3 months ago

I feel like Avro might be a contender too, but I’m leaning towards Parquet since it’s columnar storage.

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Matthew

4 months ago

I remember practicing with CSV and JSON formats, but they often lose precision with floating-point numbers.

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Huey

4 months ago

I think Parquet is the right choice because it’s optimized for storing complex data types, but I’m not completely sure.

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Veronique

4 months ago

I'm pretty sure Parquet is designed to efficiently store numerical data, so that's my best guess for the answer.

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Ollie

4 months ago

JSON is more for structured data, so I doubt it would be the best choice for preserving floating-point precision.

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Marleen

4 months ago

CSV is a common format, but it's not great for preserving data types, so I don't think that's the answer.

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Elin

5 months ago

Okay, I know Avro and Parquet are both popular big data file formats, so I'll focus on those two options.

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Angella

5 months ago

Hmm, this one seems tricky. I'll need to think carefully about the different file formats and how they handle floating-point numbers.

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Lettie

8 months ago

I would go with D) Parquet as well, it supports advanced data types and is optimized for performance.

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Yoko

9 months ago

JSON? Are we building a rocket or analyzing data? Parquet is the clear winner here.

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Julene

7 months ago

JSON might be good for other purposes, but when it comes to unloading data, Parquet is the way to go.

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Breana

8 months ago

I agree, Parquet is optimized for efficient storage and processing of columnar data.

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Colton

8 months ago

Parquet is definitely the best choice for preserving data values for floating-point numbers.

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Natalie

9 months ago

I'm not sure, but I think Avro is also a good option for preserving data values.

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Levi

9 months ago

I agree with Ronnie, Parquet is designed to efficiently store nested data structures.

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Ceola

10 months ago

CSV? More like 'Can't Save Values'. Parquet is the answer, hands down.

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Penney

10 months ago

Avro? Nah, that's for space aliens. Parquet is the way to go for those precious floating-point numbers.

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Shizue

9 months ago

Avro may be for space aliens, but Parquet is the real deal for floating-point numbers.

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Paulene

9 months ago

I agree, Parquet is the way to go for sure.

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Jaleesa

9 months ago

Parquet is definitely the best choice for preserving floating-point numbers.

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Ronnie

10 months ago

I think the answer is D) Parquet.

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