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Snowflake ARA-C01 Exam Syllabus Topics:

Section	Objectives
Data Sharing and Collaboration	- Secure data sharing 1. Cross-account data sharing 2. Data marketplace concepts
Data Pipelines and Data Engineering	- Data ingestion and transformation 1. Snowpipe and continuous data loading 2. Batch and streaming ingestion - Data orchestration 1. Tasks and Streams usage 2. Pipeline design patterns
Performance and Optimization	- Query performance tuning 1. Warehouse sizing and scaling 2. Query profiling and optimization techniques - Cost optimization 1. Storage and compute efficiency 2. Resource monitoring and cost control
Data Architecture and Design	- Data modeling and schema design 1. Semi-structured data modeling 2. Star and snowflake schema concepts - Design scalable Snowflake architectures 1. Multi-cluster virtual warehouse design 2. Account and environment strategy
Security, Governance, and Compliance	- Data governance 1. Data classification and masking policies 2. Audit and compliance features - Access control and security model 1. Role-based access control (RBAC) 2. Network security and authentication

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q57-Q62):

NEW QUESTION # 57
A table for IOT devices that measures water usage is created. The table quickly becomes large and contains more than 2 billion rows.

The general query patterns for the table are:
1. DeviceId, lOT_timestamp and Customerld are frequently used in the filter predicate for the select statement
2. The columns City and DeviceManuf acturer are often retrieved
3. There is often a count on Uniqueld
Which field(s) should be used for the clustering key?

A. Uniqueld
B. lOT_timestamp
C. Deviceld and Customerld
D. City and DeviceManuf acturer

Answer: C

NEW QUESTION # 58
Role A has the following permissions:
. USAGE on db1
. USAGE and CREATE VIEW on schemal in db1
. SELECT on tablel in schemal
Role B has the following permissions:
. USAGE on db2
. USAGE and CREATE VIEW on schema2 in db2
. SELECT on table2 in schema2
A user has Role A set as the primary role and Role B as a secondary role.
What command will fail for this user?

A. use database db1;use schema schemal;select * from db2.schema2.table2;
B. use database db2;use schema schema2;create view v2 as select * from dbl.schemal. tablel;
C. use database db1;use schema schemal;create view v1 as select * from db2.schema2.table2;
D. use database db2;use schema schema2;select * from db1.schemal.tablel union select * from table2;

Answer: B

Explanation:
This command will fail because while the user has USAGE permission ondb2andschema2through Role B, and can create a view inschema2, they do not have SELECT permission ondb1.schemal.table1with Role B.
Since Role A, which has SELECT permission ondb1.schemal.table1, is not the currently active role when the viewv2is being created indb2.schema2, the user does not have the necessary permissions to read fromdb1.
schemal.table1to create the view. Snowflake's security model requires that the active role have all necessary permissions to execute the command.

NEW QUESTION # 59
What is the data size limit for loading into a variant column?

A. 1 GB(Compressed)
B. 32 GB
C. 10 MB - 100 MB compressed
D. 16 MB(Compressed)

Answer: D

NEW QUESTION # 60
How can the Snowflake context functions be used to help determine whether a user is authorized to see data that has column-level security enforced? (Select TWO).

A. Set masking policy conditions using is_role_in_session targeting the role in use for the current account.
B. Determine if there are ownership privileges on the masking policy that would allow the use of any function.
C. Set masking policy conditions using invoker_role targeting the executing role in a SQL statement.
D. Assign the accountadmin role to the user who is executing the object.
E. Set masking policy conditions using current_role targeting the role in use for the current session.

Answer: C,E

NEW QUESTION # 61
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?

A. Use materialized views and pre-calculate the data.
B. Increase the warehouse to size Large and set auto_suspend = 600.
C. Use a multi-cluster warehouse in auto-scale mode with 1 size Medium cluster, and set min_cluster_count = 1 and max_cluster_count = 4.
D. Use a multi-cluster warehouse in maximized mode with 2 size Medium clusters.

Answer: C

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.
Reference: Snowflake's official documentation on managing warehouses and using auto-scaling features.

NEW QUESTION # 62
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