Snowflake Exam ARA-C01 Topic 2 Question 43 Discussion

Actual exam question for Snowflake's ARA-C01 exam

Question #: 43
Topic #: 2

The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:

1) Finance and Vendor Management team members who require reporting and visualization

2) Data Science team members who require access to raw data for ML model development

3) Sales team members who require engineered and protected data for data monetization

What Snowflake data modeling approaches will meet these requirements? (Choose two.)

AConsolidate data in the company's data lake and use EXTERNAL TABLES.

BCreate a raw database for landing and persisting raw data entering the data pipelines.

CCreate a set of profile-specific databases that aligns data with usage patterns.

DCreate a single star schema in a single database to support all consumers' requirements.

ECreate a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.

Show Suggested Answer

Suggested Answer: C

Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.

Reference =

* Snowflake Documentation on micro-partitions and data clustering2

* Community article on recognizing unsatisfactory pruning and improving it1

by Della at Dec 09, 2024, 11:58 AM

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Socorro

18 days ago

Ah, the age-old debate: centralize everything or distribute by use case? I'm leaning towards C and B - keep the raw data separate, but build out those profile-specific databases to make everyone's lives easier.

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Florinda

19 days ago

E is definitely the most elegant solution, but I'm not sure the sales team is going to be thrilled about having to go through the Vault for their data monetization needs. C and B seem like they strike a better balance.

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Cherelle

24 days ago

Haha, I bet the finance team is going to love having to access the raw data in the Data Vault! 'Sorry, can't give you that report, you'll have to dig through the Vault.'

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Gaston

9 days ago

B) Create a raw database for landing and persisting raw data entering the data pipelines.

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Willodean

20 days ago

A) Consolidate data in the company's data lake and use EXTERNAL TABLES.

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2 months ago

I think options B and C could meet the requirements.

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