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Snowflake ARA-C01 Exam Questions

Exam Name: SnowPro Advanced: Architect Certification Exam
Exam Code: ARA-C01
Related Certification(s): Snowflake SnowPro Certification
Certification Provider: Snowflake
Actual Exam Duration: 115 Minutes
Number of ARA-C01 practice questions in our database: 162 (updated: Feb. 05, 2025)
Expected ARA-C01 Exam Topics, as suggested by Snowflake :
  • Topic 1: Design data sharing solutions, based on different use cases/ Determine the appropriate data transformation solution to meet business needs
  • Topic 2: Design a Snowflake account and database strategy, based on business requirements/ Troubleshoot performance issues with existing architectures
  • Topic 3: Outline the benefits and limitations of various data models in a Snowflake environment/ Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake
  • Topic 4: Outline performance tools, best practices, and appropriate scenarios where they should be applied/ Determine the appropriate data recovery solution in Snowflake and how data can be restored
  • Topic 5: Determine the appropriate data loading or data unloading solution to meet business needs/ Design an architecture that meets data security, privacy, compliance, and governance requirements
  • Topic 6: Create architecture solutions that support Development Lifecycles as well as workload requirements/ Outline Snowflake security principles and identify use cases where they should be applied
Disscuss Snowflake ARA-C01 Topics, Questions or Ask Anything Related

Kati

13 days ago
Passed with flying colors! Know Snowflake's data loading options inside out, including Snowpipe and bulk loading strategies. Pass4Success's comprehensive coverage was a lifesaver.
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Carole

14 days ago
Just became a SnowPro Advanced Architect! Pass4Success materials were key to my success. Accurate and time-saving.
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Graciela

19 days ago
Just passed the Snowflake SnowPro Advanced: Architect Certification Exam! The Pass4Success practice questions were a lifesaver. One challenging question was about performance optimization, specifically the impact of micro-partitioning on query performance. I wasn't sure about the best practices, but I managed to pass.
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Fausto

28 days ago
The exam includes scenarios on optimizing query performance. Understand how to use clustering keys and search optimization effectively. Pass4Success's questions helped me nail this section.
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Nickole

1 months ago
Be ready to design solutions using Snowflake's time travel and fail-safe features. The exam tests your ability to plan data recovery strategies. Pass4Success's practice exams covered this perfectly.
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Shayne

1 months ago
Snowflake Architect certified! Pass4Success made it possible with their up-to-date question bank. Couldn't have done it without them.
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Cory

1 months ago
I passed the Snowflake SnowPro Advanced: Architect Certification Exam, thanks to the Pass4Success practice questions. There was a tricky question about data engineering, particularly the use of Snowpipe for continuous data ingestion. I wasn't entirely confident about the configuration details, but I still passed.
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Truman

2 months ago
Just cleared the exam! There were questions on Snowflake's replication and failover strategies. Study cross-region and cross-cloud replication scenarios. Pass4Success really prepared me well for this.
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Kayleigh

2 months ago
Excited to share that I passed the Snowflake SnowPro Advanced: Architect Certification Exam. The practice questions from Pass4Success were extremely helpful. One question that caught me off guard was about the architecture of Snowflake, specifically the role of the metadata service. I wasn't completely sure about its functions, but I passed the exam.
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Yoko

2 months ago
The exam covers Snowflake's data governance features in depth. Make sure you understand how to implement row-access policies and column-level security. Pass4Success's materials were crucial here.
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Julian

2 months ago
Success! Passed the Snowflake Architect certification. Pass4Success questions were incredibly similar to the real thing. Time well spent!
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Ettie

3 months ago
I successfully passed the Snowflake SnowPro Advanced: Architect Certification Exam. The Pass4Success practice questions were a great resource. There was a question about configuring network policies for account security. I was unsure about the exact steps to restrict access to specific IP ranges, but I managed to pass.
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Elliott

3 months ago
Don't underestimate the importance of understanding Snowflake's account structure and hierarchy. The exam asks about organization and account management. Pass4Success helped me master this area.
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Zana

3 months ago
Thrilled to announce that I passed the Snowflake SnowPro Advanced: Architect Certification Exam. The practice questions from Pass4Success were invaluable. One question that puzzled me was about query performance optimization, specifically the use of result caching. I wasn't certain about the conditions under which result caching is most effective, but I still passed.
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Rolande

3 months ago
Aced the SnowPro Advanced exam! Pass4Success practice tests were a lifesaver. Highly recommend for quick, effective prep.
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Johnetta

3 months ago
Passed the exam! Be prepared for questions on Snowflake's security features, especially around network policies and IP whitelisting. Pass4Success's practice questions were spot-on for this topic.
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Jolanda

4 months ago
I passed the Snowflake SnowPro Advanced: Architect Certification Exam, and the Pass4Success practice questions were a big help. There was a question about the best practices for data transformation in Snowflake. I wasn't entirely sure about the optimal use of streams and tasks, but I managed to get through.
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Patrick

4 months ago
The exam tests your knowledge of Snowflake's storage integration options. Study how to set up and manage external stages with different cloud providers. Thanks to Pass4Success for covering this thoroughly!
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Noble

4 months ago
Happy to share that I passed the Snowflake SnowPro Advanced: Architect Certification Exam. The Pass4Success practice questions were very useful. One challenging question was about the different components of Snowflake's architecture, specifically the role of the virtual warehouse. I was a bit unsure about the details, but I passed nonetheless.
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Wade

4 months ago
Whew, that Snowflake Architect cert was tough! Grateful for Pass4Success materials - they really matched the actual exam content.
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Hollis

4 months ago
Exam tip: Be ready to explain Snowflake's data sharing capabilities. Know the differences between standard, reader accounts, and data exchange. Pass4Success really helped me grasp these concepts!
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Arminda

5 months ago
Just cleared the Snowflake SnowPro Advanced: Architect Certification Exam! The practice questions from Pass4Success were a huge help. There was a tricky question about setting up multi-factor authentication (MFA) for account security. I wasn't confident about the exact steps to enforce MFA, but I still made it through.
upvoted 0 times
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Layla

5 months ago
Just passed the SnowPro Advanced: Architect exam! Grateful for Pass4Success's relevant questions that helped me prepare quickly. Watch out for questions on Snowflake's multi-cluster warehouse architecture - understand how it scales compute resources.
upvoted 0 times
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Mable

5 months ago
I recently passed the Snowflake SnowPro Advanced: Architect Certification Exam, and it was quite a journey. The Pass4Success practice questions were instrumental in my preparation. One question that stumped me was about optimizing query performance using clustering keys. I wasn't entirely sure how to choose the best clustering key for a given dataset, but I managed to pass the exam.
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Rozella

5 months ago
Just passed the SnowPro Advanced: Architect exam! Thanks Pass4Success for the spot-on practice questions. Saved me weeks of prep time!
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Thaddeus

6 months ago
Passing the Snowflake SnowPro Advanced: Architect Certification Exam was a great accomplishment for me, and I couldn't have done it without the help of Pass4Success practice questions. One question that I found particularly challenging was related to designing a Snowflake account and database strategy based on business requirements. It required me to consider various factors such as scalability, security, and cost efficiency in my design.
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Olive

7 months ago
Successfully cleared the exam! Performance optimization was a major topic. Expect to analyze query plans and suggest improvements for complex joins and aggregations. Review Snowflake's query profiling tools and caching mechanisms. Grateful for Pass4Success's relevant practice material that saved me time!
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Gianna

7 months ago
My experience taking the Snowflake SnowPro Advanced: Architect Certification Exam was intense, but I managed to pass with the assistance of Pass4Success practice questions. One question that I remember was about troubleshooting performance issues with existing architectures. It required me to analyze a given architecture and identify potential bottlenecks that could be impacting performance.
upvoted 0 times
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German

8 months ago
I recently passed the Snowflake SnowPro Advanced: Architect Certification Exam with the help of Pass4Success practice questions. The exam was challenging, but I felt well-prepared thanks to the practice questions. One question that stood out to me was related to designing data sharing solutions based on different use cases. It required me to think critically about the best approach for a given scenario.
upvoted 0 times
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Jaclyn

8 months ago
SnowPro Advanced: Architect exam conquered! Pass4Success's practice questions were key to my success. Appreciate the time-saving resources!
upvoted 0 times
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Dorathy

8 months ago
Passed the Snowflake Architect exam today! Pass4Success's questions were incredibly similar to the real thing. Thanks for the quick prep!
upvoted 0 times
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Belen

8 months ago
The exam dived deep into data governance strategies. Be prepared for scenarios on implementing row-level security and dynamic data masking at scale. Brush up on Snowflake's security features and best practices for large enterprises. Pass4Success really helped me prepare efficiently!
upvoted 0 times
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Lindsey

8 months ago
Just passed the SnowPro Advanced: Architect exam! Pass4Success's practice questions were spot-on. Thanks for helping me prepare so quickly!
upvoted 0 times
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Rickie

8 months ago
Wow, the Snowflake Architect exam was tough, but I made it! Grateful for Pass4Success's relevant practice material. Saved me so much time!
upvoted 0 times
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Gennie

9 months ago
SnowPro Advanced: Architect certified! Pass4Success's exam questions were a lifesaver. Couldn't have done it without their efficient prep materials.
upvoted 0 times
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Stephania

10 months ago
Just passed the SnowPro Advanced: Architect exam! A key focus was on multi-cloud architecture. Expect questions on designing resilient, cross-cloud deployments. Study Snowflake's replication and failover features across different cloud providers. Thanks to Pass4Success for the spot-on practice questions!
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Free Snowflake ARA-C01 Exam Actual Questions

Note: Premium Questions for ARA-C01 were last updated On Feb. 05, 2025 (see below)

Question #1

Two queries are run on the customer_address table:

create or replace TABLE CUSTOMER_ADDRESS ( CA_ADDRESS_SK NUMBER(38,0), CA_ADDRESS_ID VARCHAR(16), CA_STREET_NUMBER VARCHAR(IO) CA_STREET_NAME VARCHAR(60), CA_STREET_TYPE VARCHAR(15), CA_SUITE_NUMBER VARCHAR(10), CA_CITY VARCHAR(60), CA_COUNTY

VARCHAR(30), CA_STATE VARCHAR(2), CA_ZIP VARCHAR(10), CA_COUNTRY VARCHAR(20), CA_GMT_OFFSET NUMBER(5,2), CA_LOCATION_TYPE

VARCHAR(20) );

ALTER TABLE DEMO_DB.DEMO_SCH.CUSTOMER_ADDRESS ADD SEARCH OPTIMIZATION ON SUBSTRING(CA_ADDRESS_ID);

Which queries will benefit from the use of the search optimization service? (Select TWO).

Reveal Solution Hide Solution
Correct Answer: A, B

The use of the search optimization service in Snowflake is particularly effective when queries involve operations that match exact substrings or start from the beginning of a string. The ALTER TABLE command adding search optimization specifically for substrings on the CA_ADDRESS_ID field allows the service to create an optimized search path for queries using substring matches.

Option A benefits because it directly matches a substring from the start of the CA_ADDRESS_ID, aligning with the optimization's capability to quickly locate records based on the beginning segments of strings.

Option B also benefits, despite performing a full equality check, because it essentially compares the full length of CA_ADDRESS_ID to a substring, which can leverage the substring index for efficient retrieval. Options C, D, and E involve patterns that do not start from the beginning of the string or use negations, which are not optimized by the search optimization service configured for starting substring matches. Reference: Snowflake's documentation on the use of search optimization for substring matching in SQL queries.


Question #2

A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.

The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.

What step can be taken to improve the pruning of the reporting tables?

Reveal Solution Hide Solution
Correct 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


Question #3

The data share exists between a data provider account and a data consumer account. Five tables from the provider account are being shared with the consumer account. The consumer role has been granted the imported privileges privilege.

What will happen to the consumer account if a new table (table_6) is added to the provider schema?

Reveal Solution Hide Solution
Correct Answer: D

When a new table (table_6) is added to a schema in the provider's account that is part of a data share, the consumer will not automatically see the new table. The consumer will only be able to access the new table once the appropriate privileges are granted by the provider. The correct process, as outlined in option D, involves using the provider's ACCOUNTADMIN role to grant USAGE privileges on the database and schema, followed by SELECT privileges on the new table, specifically to the share that includes the consumer's database. This ensures that the consumer account can access the new table under the established data sharing setup. Reference:

Snowflake Documentation on Managing Access Control

Snowflake Documentation on Data Sharing


Question #4

A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.

The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.

What step can be taken to improve the pruning of the reporting tables?

Reveal Solution Hide Solution
Correct 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


Question #5

A company has a source system that provides JSON records for various loT operations. The JSON Is loading directly into a persistent table with a variant field. The data Is quickly growing to 100s of millions of records and performance to becoming an issue. There is a generic access pattern that Is used to filter on the create_date key within the variant field.

What can be done to improve performance?

Reveal Solution Hide Solution
Correct Answer: A

The correct answer is A because it improves the performance of queries by reducing the amount of data scanned and processed. By adding a create_date field with a timestamp data type, Snowflake can automatically cluster the table based on this field and prune the micro-partitions that do not match the filter condition. This avoids the need to parse the JSON data and access the variant field for every record.

Option B is incorrect because it does not improve the performance of queries. By adding a create_date field with a varchar data type, Snowflake cannot automatically cluster the table based on this field and prune the micro-partitions that do not match the filter condition. This still requires parsing the JSON data and accessing the variant field for every record.

Option C is incorrect because it does not address the root cause of the performance issue. By validating the size of the warehouse being used, Snowflake can adjust the compute resources to match the data volume and parallelize the query execution. However, this does not reduce the amount of data scanned and processed, which is the main bottleneck for queries on JSON data.

Option D is incorrect because it adds unnecessary complexity and overhead to the data loading and querying process. By incorporating the use of multiple tables partitioned by date ranges, Snowflake can reduce the amount of data scanned and processed for queries that specify a date range. However, this requires creating and maintaining multiple tables, loading data into the appropriate table based on the date, and joining the tables for queries that span multiple date ranges.Reference:

Snowflake Documentation: Loading Data Using Snowpipe: This document explains how to use Snowpipe to continuously load data from external sources into Snowflake tables. It also describes the syntax and usage of the COPY INTO command, which supports various options and parameters to control the loading behavior, such as ON_ERROR, PURGE, and SKIP_FILE.

Snowflake Documentation: Date and Time Data Types and Functions: This document explains the different data types and functions for working with date and time values in Snowflake. It also describes how to set and change the session timezone and the system timezone.

Snowflake Documentation: Querying Metadata: This document explains how to query the metadata of the objects and operations in Snowflake using various functions, views, and tables. It also describes how to access the copy history information using the COPY_HISTORY function or the COPY_HISTORY view.

Snowflake Documentation: Loading JSON Data: This document explains how to load JSON data into Snowflake tables using various methods, such as the COPY INTO command, the INSERT command, or the PUT command. It also describes how to access and query JSON data using the dot notation, the FLATTEN function, or the LATERAL join.

Snowflake Documentation: Optimizing Storage for Performance: This document explains how to optimize the storage of data in Snowflake tables to improve the performance of queries. It also describes the concepts and benefits of automatic clustering, search optimization service, and materialized views.



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