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Snowflake ARA-C01 Certification Exam consists of 60 multiple-choice questions and has a time limit of 120 minutes. ARA-C01 exam is administered online and can be taken from anywhere in the world. The passing score for the exam is 80%, and individuals who pass the exam will receive the SnowPro Advanced Architect Certification. SnowPro Advanced Architect Certification certification is recognized globally and demonstrates that the holder has the skills and knowledge to design and deploy complex Snowflake solutions that meet the needs of their organization. The SnowPro Advanced Architect Certification is a valuable credential for data architects, data engineers, and data analysts who work with Snowflake and want to advance their careers in the field of data management and analytics.

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Snowflake ARA-C01 certification exam is designed to validate the advanced skills and knowledge of individuals in designing and implementing complex Snowflake data warehousing solutions. SnowPro Advanced Architect Certification certification exam is intended for Snowflake architects who have experience in designing and implementing Snowflake solutions in a variety of environments. The Snowflake ARA-C01 Certification Exam is a challenging exam that requires a good understanding of Snowflake architecture, data modeling, and performance optimization.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q25-Q30):

NEW QUESTION # 25
An Architect needs to improve the performance of reports that pull data from multiple Snowflake tables, join, and then aggregate the data. Users access the reports using several dashboards. There are performance issues on Monday mornings between 9:00am-11:00am when many users check the sales reports.
The size of the group has increased from 4 to 8 users. Waiting times to refresh the dashboards has increased significantly. Currently this workload is being served by a virtual warehouse with the following parameters:
AUTO-RESUME = TRUE AUTO_SUSPEND = 60 SIZE = Medium
What is the MOST cost-effective way to increase the availability of the reports?

Answer: D

Explanation:
The most cost-effective way to increase the availability and performance of the reports during peak usage times, while keeping costs under control, is to use a multi-cluster warehouse in auto-scale mode. Option D suggests using a multi-cluster warehouse with 1 size Medium cluster and allowing it to auto-scale between 1 and 4 clusters based on demand. This setup ensures that additional computing resources are available when needed (e.g., during Monday morning peaks) and are scaled down to minimize costs when the demand decreases. This approach optimizes resource utilization and cost by adjusting the compute capacity dynamically, rather than maintaining a larger fixed size or multiple clusters continuously.
References:Snowflake's official documentation on managing warehouses and using auto-scaling features.


NEW QUESTION # 26
An Architect would like to save quarter-end financial results for the previous six years.
Which Snowflake feature can the Architect use to accomplish this?

Answer: A


NEW QUESTION # 27
You are a snowflake architect in an organization. The business team came to to deploy an use case which requires you to load some data which they can visualize through tableau. Everyday new data comes in and the old data is no longer required.
What type of table you will use in this case to optimize cost

Answer: C

Explanation:
Explanation
* A transient table is a type of table in Snowflake that does not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. Transient tables are suitable for temporary or intermediate data that can be easily reproduced or replicated1.
* A temporary table is a type of table in Snowflake that is automatically dropped when the session ends or the current user logs out. Temporary tables do not incur any storage costs, but they are not visible to other users or sessions2.
* A permanent table is a type of table in Snowflake that has a Fail-safe period and a Time Travel retention period of up to 90 days. Permanent tables are suitable for persistent and durable data that needs to be protected from accidental or malicious deletion3.
* In this case, the use case requires loading some data that can be visualized through Tableau. The data is updated every day and the old data is no longer required. Therefore, the best type of table to use in this case to optimize cost is a transient table, because it does not incur any Fail-safe costs and it can have a short Time Travel retention period of 0 or 1 day. This way, the data can be loaded and queried by Tableau, and then deleted or overwritten without incurring any unnecessary storage costs.
References: : Transient Tables : Temporary Tables : Understanding & Using Time Travel


NEW QUESTION # 28
How can an Architect enable optimal clustering to enhance performance for different access paths on a given table?

Answer: C

Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the best way to enable optimal clustering to enhance performance for different access paths on a given table is to create multiple materialized views with different cluster keys. A materialized view is a pre-computed result set that is derived from a query on one or more base tables. A materialized view can be clustered by specifying a clustering key, which is a subset of columns or expressions that determines how the data in the materialized view is co- located in micro-partitions. By creating multiple materialized views with different cluster keys, an Architect can optimize the performance of queries that use different access paths on the same base table. For example, if a base table has columns A, B, C, and D, and there are queries that filter on A and B, or on C and D, or on A and C, the Architect can create three materialized views, each with a different cluster key: (A, B), (C, D), and (A, C). This way, each query can leverage the optimal clustering of the corresponding materialized view and achieve faster scan efficiency and better compression.
Snowflake Documentation: Materialized Views
Snowflake Learning: Materialized Views
https://www.snowflake.com/blog/using-materialized-views-to-solve-multi-clustering-performance-problems/


NEW QUESTION # 29
How can an Architect enable optimal clustering to enhance performance for different access paths on a given table?

Answer: A

Explanation:
Snowflake allows only one clustering key per table, which limits its effectiveness when multiple access paths exist. Creating a composite clustering key that includes many columns often leads to poor clustering depth and limited pruning.
Materialized views provide an effective alternative. Each materialized view can be clustered independently, allowing architects to tailor physical data organization to specific query patterns (Answer B). Queries targeting different access paths can then leverage the appropriate materialized view, achieving better pruning and performance.
Super projections are not a Snowflake feature. Creating multiple clustering keys on a single table is not supported. This question reinforces SnowPro Architect knowledge of advanced performance design techniques using materialized views.
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NEW QUESTION # 30
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