Snowflake ARA-C01 Practice Exams
Last updated on Oct 21,2026- Exam Code: ARA-C01
- Exam Name: SnowPro Advanced Architect Certification
- Certification Provider: Snowflake
- Latest update: Oct 21,2026
A retailer’s enterprise data organization is exploring the use of Data Vault 2.0 to model its data lake solution. A Snowflake Architect has been asked to provide recommendations for using Data Vault 2.0 on Snowflake.
What should the Architect tell the data organization? (Select TWO).
- A . Change data capture can be performed using the Data Vault 2.0 HASH_DIFF concept.
- B . Change data capture can be performed using the Data Vault 2.0 HASH_DELTA concept.
- C . Using the multi-table insert feature in Snowflake, multiple Point-in-Time (PIT) tables can be loaded in parallel from a single join query from the data vault.
- D . Using the multi-table insert feature, multiple Point-in-Time (PIT) tables can be loaded sequentially from a single join query from the data vault.
- E . There are performance challenges when using Snowflake to load multiple Point-in-Time (PIT) tables in parallel from a single join query from the data vault.
A, C
Explanation:
Data Vault 2.0 on Snowflake supports the HASH_DIFF concept for change data capture, which is a method to detect changes in the data by comparing the hash values of the records. Additionally, Snowflake’s multi-table insert feature allows for the loading of multiple PIT tables in parallel from a single join query, which can significantly streamline the data loading process and improve performance1.
Reference =
• Snowflake’s documentation on multi-table inserts1
• Blog post on optimizing Data Vault architecture on Snowflake2
A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?
- A . Create accounts for each tenant in the Snowflake organization.
- B . Create an object for each tenant strategy if row level security is viable for isolating tenants.
- C . Create an object for each tenant strategy if row level security is not viable for isolating tenants.
- D . Create a multi-tenant table strategy if row level security is not viable for isolating tenants.
A
Explanation:
In a scenario where strong legal isolation is required alongside the need for multi-tenancy, the most effective approach is to create separate accounts for each tenant within the Snowflake organization. This approach ensures complete isolation of data, resources, and management, adhering to strict legal and compliance requirements. Role-Based Access Control (RBAC) further enhances security by allowing granular control over who can access what resources within each account. This solution leverages Snowflake’s capabilities for managing multiple accounts under a single organization umbrella, ensuring that each tenant’s data and operations are isolated from others.
Reference: Snowflake documentation on multi-tenancy and account management, part of the SnowPro Advanced: Architect learning path.
Which feature provides the capability to define an alternate cluster key for a table with an existing cluster key?
- A . External table
- B . Materialized view
- C . Search optimization
- D . Result cache
B
Explanation:
A materialized view is a feature that provides the capability to define an alternate cluster key for a table with an existing cluster key. A materialized view is a pre-computed result set that is stored in Snowflake and can be queried like a regular table. A materialized view can have a different cluster key than the base table, which can improve the performance and efficiency of queries on the materialized view. A materialized view can also support aggregations, joins, and filters on the base table data. A materialized view is automatically refreshed when the underlying data in the base table changes, as long as the AUTO_REFRESH parameter is set to true1.
Reference: Materialized Views | Snowflake Documentation
Which feature provides the capability to define an alternate cluster key for a table with an existing cluster key?
- A . External table
- B . Materialized view
- C . Search optimization
- D . Result cache
B
Explanation:
A materialized view is a feature that provides the capability to define an alternate cluster key for a table with an existing cluster key. A materialized view is a pre-computed result set that is stored in Snowflake and can be queried like a regular table. A materialized view can have a different cluster key than the base table, which can improve the performance and efficiency of queries on the materialized view. A materialized view can also support aggregations, joins, and filters on the base table data. A materialized view is automatically refreshed when the underlying data in the base table changes, as long as the AUTO_REFRESH parameter is set to true1.
Reference: Materialized Views | Snowflake Documentation
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?
- A . Search optimization service
- B . Materialized view
- C . Time Travel
- D . Zero-copy cloning
- E . Secure views
D
Explanation:
Zero-copy cloning is a Snowflake feature that can be used to save quarter-end financial results for the previous six years. Zero-copy cloning allows creating a copy of a database, schema, table, or view without duplicating the data or metadata. The clone shares the same data files as the original object, but tracks any changes made to the clone or the original separately. Zero-copy cloning can be used to create snapshots of data at different points in time, such as quarter-end financial results, and preserve them for future analysis or comparison. Zero-copy cloning is fast, efficient, and does not consume any additional storage space unless the data is modified1.
Reference: Zero-Copy Cloning | Snowflake Documentation
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?
- A . Search optimization service
- B . Materialized view
- C . Time Travel
- D . Zero-copy cloning
- E . Secure views
D
Explanation:
Zero-copy cloning is a Snowflake feature that can be used to save quarter-end financial results for the previous six years. Zero-copy cloning allows creating a copy of a database, schema, table, or view without duplicating the data or metadata. The clone shares the same data files as the original object, but tracks any changes made to the clone or the original separately. Zero-copy cloning can be used to create snapshots of data at different points in time, such as quarter-end financial results, and preserve them for future analysis or comparison. Zero-copy cloning is fast, efficient, and does not consume any additional storage space unless the data is modified1.
Reference: Zero-Copy Cloning | Snowflake Documentation
An Architect is implementing a CI/CD process. When attempting to clone a table from a production to a development environment, the cloning operation fails.
What could be causing this to happen?
- A . The table is transient.
- B . The table has a masking policy.
- C . The retention time for the table is set to zero.
- D . Tables cannot be cloned from a higher environment to a lower environment.
B
Explanation:
Cloning a table with a masking policy can cause the cloning operation to fail because the masking policy is not automatically cloned with the table. This is due to the fact that the masking policy is considered a separate object with its own set of privileges1.
Reference: Snowflake Documentation on Cloning Considerations1.
Which SQL alter command will MAXIMIZE memory and compute resources for a Snowpark stored procedure when executed on the snowpark_opt_wh warehouse?
A)
![]()
B)
![]()
C)
![]()
D)
![]()
- A . Option A
- B . Option B
- C . Option C
- D . Option D
A
Explanation:
To maximize memory and compute resources for a Snowpark stored procedure, you need to set the MAX_CONCURRENCY_LEVEL parameter for the warehouse that executes the stored procedure. This parameter determines the maximum number of concurrent queries that can run on a single warehouse. By setting it to 16, you ensure that the warehouse can use all the available CPU cores and memory on a single node, which is the optimal configuration for Snowpark-optimized warehouses. This will improve the performance and efficiency of the stored procedure, as it will not have to share resources with other queries or nodes. The other options are incorrect because they either do not change the MAX_CONCURRENCY_LEVEL parameter, or they set it to a lower value than 16, which will reduce the memory and compute resources for the stored procedure.
Reference: [Snowpark-optimized Warehouses] 1
[Training Machine Learning Models with Snowpark Python] 2 [Snowflake Shorts: Snowpark Optimized Warehouses] 3
A retail company has 2000+ stores spread across the country. Store Managers report that they are having trouble running key reports related to inventory management, sales targets, payroll, and staffing during business hours. The Managers report that performance is poor and time-outs occur frequently.
Currently all reports share the same Snowflake virtual warehouse.
How should this situation be addressed? (Select TWO).
- A . Use a Business Intelligence tool for in-memory computation to improve performance.
- B . Configure a dedicated virtual warehouse for the Store Manager team.
- C . Configure the virtual warehouse to be multi-clustered.
- D . Configure the virtual warehouse to size 4-XL
- E . Advise the Store Manager team to defer report execution to off-business hours.
B, C
Explanation:
The best way to address the performance issues and time-outs faced by the Store Manager team is to configure a dedicated virtual warehouse for them and make it multi-clustered. This will allow them to run their reports independently from other workloads and scale up or down the compute resources as needed. A dedicated virtual warehouse will also enable them to apply specific security and access policies for their data. A multi-clustered virtual warehouse will provide high availability and concurrency for their queries and avoid queuing or throttling.
Using a Business Intelligence tool for in-memory computation may improve performance, but it will not solve the underlying issue of insufficient compute resources in the shared virtual warehouse. It will also introduce additional costs and complexity for the data architecture.
Configuring the virtual warehouse to size 4-XL may increase the performance, but it will also increase the cost and may not be optimal for the workload. It will also not address the concurrency and availability issues that may arise from sharing the virtual warehouse with other workloads. Advising the Store Manager team to defer report execution to off-business hours may reduce the load on the shared virtual warehouse, but it will also reduce the timeliness and usefulness of the reports for the business. It will also not guarantee that the performance issues and time-outs will not
occur at other times.
Reference: Snowflake Architect Training
Snowflake SnowPro Advanced Architect Certification – Preparation Guide SnowPro Advanced: Architect Exam Study Guide
Which security, governance, and data protection features require, at a MINIMUM, the Business Critical edition of Snowflake? (Choose two.)
- A . Extended Time Travel (up to 90 days)
- B . Customer-managed encryption keys through Tri-Secret Secure
- C . Periodic rekeying of encrypted data
- D . AWS, Azure, or Google Cloud private connectivity to Snowflake
- E . Federated authentication and SSO
B, D
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the security, governance, and data protection features that require, at a minimum, the Business Critical edition of Snowflake are:
Customer-managed encryption keys through Tri-Secret Secure. This feature allows customers to manage their own encryption keys for data at rest in Snowflake, using a combination of three secrets: a master key, a service key, and a security password. This provides an additional layer of security and control over the data encryption and decryption process1.
Periodic rekeying of encrypted data. This feature allows customers to periodically rotate the encryption keys for data at rest in Snowflake, using either Snowflake-managed keys or customer-managed keys. This enhances the security and protection of the data by reducing the risk of key compromise or exposure2.
The other options are incorrect because they do not require the Business Critical edition of Snowflake. Option A is incorrect because extended Time Travel (up to 90 days) is available with the Enterprise edition of Snowflake3. Option D is incorrect because AWS, Azure, or Google Cloud private connectivity to Snowflake is available with the Standard edition of Snowflake4. Option E is incorrect because federated authentication and SSO are available with the Standard edition of Snowflake5.
Reference: Tri-Secret Secure | Snowflake Documentation, Periodic Rekeying of Encrypted Data | Snowflake Documentation, Snowflake Editions | Snowflake
Documentation, Snowflake Network Policies | Snowflake Documentation, Configuring Federated Authentication and SSO | Snowflake Documentation