Snowflake ARA-C01専門試験、ARA-C01テスト問題集

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ARA-C01テスト問題集 & ARA-C01受験トレーリング

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Snowflake SnowPro Advanced Architect Certification 認定 ARA-C01 試験問題 (Q12-Q17):

質問 # 12
A Snowflake Architect is designing a multiple-account design strategy.
This strategy will be MOST cost-effective with which scenarios? (Select TWO).

A. The company needs to support different role-based access control features for the development, test, and production environments.
B. The company needs to share data between two databases, where one must support Payment Card Industry Data Security Standard (PCI DSS) compliance but the other one does not.
C. The company must use a specific network policy for certain users to allow and block given IP addresses.
D. The company wants to clone a production database that resides on AWS to a development database that resides on Azure.
E. The company security policy mandates the use of different Active Directory instances for the development, test, and production environments.

正解：B、E

解説：
B: When dealing with PCI DSS compliance, having separate accounts can be beneficial because it enables strong isolation of environments that handle sensitive data from those that do not. By segregating the compliant from non-compliant resources, an organization can limit the scope of compliance, thus making it a cost-effective strategy.D. Different Active Directory instances can be managed more effectively and securely when separated into different accounts. This approach allows for distinct identity and access management policies, which can enforce security requirements and minimize the risk of access policy errors between environments.

質問 # 13
A Snowflake Architect created a new data share and would like to verify that only specific records in secure views are visible within the data share by the consumers.
What is the recommended way to validate data accessibility by the consumers?

A. Create reader accounts as shown below and impersonate the consumers by logging in with their credentials.
create managed account reader_acctl admin_name = userl , adroin_password 'Sdfed43da!44T , type = reader;
B. Set the session parameter called SIMULATED_DATA_SHARING_C0NSUMER as shown below in order to impersonate the consumer accounts.
alter session set simulated_data_sharing_consumer - 'Consumer Acctl*
C. Create a row access policy as shown below and assign it to the data share.
create or replace row access policy rap_acct as (acct_id varchar) returns boolean -> case when 'acctl_role' = current_role() then true else false end;
D. Alter the share settings as shown below, in order to impersonate a specific consumer account.
alter share sales share set accounts = 'Consumerl' share restrictions = true

正解：B

解説：
The SIMULATED_DATA_SHARING_CONSUMER session parameter allows a data provider to simulate the data access of a consumer account without creating a reader account or logging in with the consumer credentials. This parameter can be used to validate the data accessibility by the consumers in a data share, especially when using secure views or secure UDFs that filter data based on the current account or role. By setting this parameter to the name of a consumer account, the data provider can see the same data as the consumer would see when querying the shared database. This is a convenient and efficient way to test the data sharing functionality and ensure that only the intended data is visible to the consumers.
Reference:
Using the SIMULATED_DATA_SHARING_CONSUMER Session Parameter
SnowPro Advanced: Architect Exam Study Guide

質問 # 14
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 not viable for isolating tenants.
C. Create an object for each tenant strategy if row level security is viable for isolating tenants.
D. Create a multi-tenant table strategy if row level security is not viable for isolating tenants.

正解：A

解説：
This approach meets the requirements of strong legal isolation and multi-tenancy. By creating separate accounts for each tenant, the application can ensure that each tenant has its own dedicated storage, compute, and metadata resources, as well as its own encryption keys and security policies. This provides the highest level of isolation and data protection among the tenancy models. Furthermore, by creating the accounts within the same Snowflake organization, the application can leverage the features of Snowflake Organizations, such as centralized billing, account management, and cross-account data sharing.
References:
* Snowflake Organizations Overview | Snowflake Documentation
* Design Patterns for Building Multi-Tenant Applications on Snowflake

質問 # 15
At which object type level can the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges be granted?

A. Global
B. Table
C. Database
D. Schema

正解：A

解説：
The object type level at which the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY and APPLY SESSION POLICY privileges can be granted is global. These are account-level privileges that control who can apply or unset these policies on objects such as columns, tables, views, accounts, or users.
These privileges are granted to the ACCOUNTADMIN role by default, and can be granted to other roles as needed. The other options are incorrect because they are not the object type level at which these privileges can be granted. Database, schema, and table are lower-level object types that do not support these privileges. References: Access Control Privileges | Snowflake Documentation, Using Dynamic Data Masking
| Snowflake Documentation, Using Row Access Policies | Snowflake Documentation, Using Session Policies | Snowflake Documentation

質問 # 16
The following table exists in the production database:
A regulatory requirement states that the company must mask the username for events that are older than six months based on the current date when the data is queried.
How can the requirement be met without duplicating the event data and making sure it is applied when creating views using the table or cloning the table?

A. Use a masking policy on the username column using a entitlement table with valid dates.
B. Use a row level policy on the user_events table using a entitlement table with valid dates.
C. Use a secure view on the user_events table using a case statement on the username column.
D. Use a masking policy on the username column with event_timestamp as a conditional column.

正解：D

解説：
A masking policy is a feature of Snowflake that allows masking sensitive data in query results based on the role of the user and the condition of the data. A masking policy can be applied to a column in a table or a view, and it can use another column in the same table or view as a conditional column. A conditional column is a column that determines whether the masking policy is applied or not based on its value1.
In this case, the requirement can be met by using a masking policy on the username column with event_timestamp as a conditional column. The masking policy can use a function that masks the username if the event_timestamp is older than six months based on the current date, and returns the original username otherwise. The masking policy can be applied to the user_events table, and it will also be applied when creating views using the table or cloning the table2.
The other options are not correct because:
* A. Using a masking policy on the username column using an entitlement table with valid dates would require creating another table that stores the valid dates for each username, and joining it with the user_events table in the masking policy function. This would add complexity and overhead to the masking policy, and it would not use the event_timestamp column as the condition for masking.
* B. Using a row level policy on the user_events table using an entitlement table with valid dates would require creating another table that stores the valid dates for each username, and joining it with the user_events table in the row access policy function. This would filter out the rows that have event_timestamp older than six months based on the valid dates, instead of masking the username column. This would not meet the requirement of masking the username, and it would also reduce the visibility of the event data.
* D. Using a secure view on the user_events table using a case statement on the username column would require creating a view that uses a case expression to mask the username column based on the event_timestamp column. This would meet the requirement of masking the username, but it would not be applied when cloning the table. A secure view is a view that prevents the underlying data from being exposed by queries on the view. However, a secure view does not prevent the underlying data from being exposed by cloning the table3.
References:
* 1: Masking Policies | Snowflake Documentation
* 2: Using Conditional Columns in Masking Policies | Snowflake Documentation
* 3: Secure Views | Snowflake Documentation

質問 # 17
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ARA-C01テスト問題集: https://www.certjuken.com/ARA-C01-exam.html

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