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Snowflake Exam ARA-C01 Topic 2 Question 43 Discussion

Actual exam question for Snowflake's ARA-C01 exam
Question #: 43
Topic #: 2
[All ARA-C01 Questions]

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.)

Show Suggested Answer Hide 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


Contribute your Thoughts:

Gearldine
2 days ago
I think options B and C could meet the requirements.
upvoted 0 times
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