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【General】 Pdf ARA-C01 Braindumps | ARA-C01 Dumps Download

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Snowflake ARA-C01 Certification Exam is a rigorous exam that requires a significant amount of preparation and study. Candidates are expected to have a deep understanding of Snowflake architecture, best practices, and design principles. ARA-C01 exam also requires candidates to have hands-on experience with Snowflake and the ability to troubleshoot complex issues. SnowPro Advanced Architect Certification certification is an excellent way for architects to demonstrate their expertise in Snowflake and differentiate themselves from their peers.
To earn the Snowflake ARA-C01 certification, candidates must pass a rigorous exam that covers a wide range of topics related to Snowflake architecture and functionality. ARA-C01 exam consists of 60 multiple-choice questions and is timed for 90 minutes. ARA-C01 Exam is computer-based and can be taken at any authorized testing center or remotely from a candidate's home or office.
Snowflake ARA-C01 certification exam consists of 100 multiple-choice questions that are designed to test the knowledge and skills of the candidates across various domains such as data modeling, data loading, performance tuning, security and access control, and data processing. ARA-C01 exam is conducted in a timed format and candidates are expected to complete it within two hours. SnowPro Advanced Architect Certification certification exam is proctored and can be taken online from anywhere in the world.
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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q145-Q150):NEW QUESTION # 145
A user has the appropriate privilege to see unmasked data in a column.
If the user loads this column data into another column that does not have a masking policy, what will occur?
  • A. Masked data will be loaded into the new column.
  • B. Unmasked data will be loaded into the new column but only users with the appropriate privileges will be able to see the unmasked data.
  • C. Unmasked data will be loaded in the new column.
  • D. Unmasked data will be loaded into the new column and no users will be able to see the unmasked data.
Answer: C
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, column masking policies are applied at query time based on the privileges of the user who runs the query. Therefore, if a user has the privilege to see unmasked data in a column, they will see the original data when they query that column. If they load this column data into another column that does not have a masking policy, the unmasked data will be loaded in the new column, and any user who can query the new column will see the unmasked data as well.
The masking policy does not affect the underlying data in the column, only the query results.
References:
* Snowflake Documentation: Column Masking
* Snowflake Learning: Column Masking

NEW QUESTION # 146
Consider the following scenario where a masking policy is applied on the CREDICARDND column of the CREDITCARDINFO table. The masking policy definition Is as follows:

Sample data for the CREDITCARDINFO table is as follows:
NAME EXPIRYDATE CREDITCARDNO
JOHN DOE 2022-07-23 4321 5678 9012 1234
if the Snowflake system rotes have not been granted any additional roles, what will be the result?
  • A. Anyone with the Pl_ANALYTICS role will see the CREDICARDND column as*** 'MASKED* **'.
  • B. The owner of the table will see the CREDICARDND column data in clear text.
  • C. The sysadmin can see the CREDICARDND column data in clear text.
  • D. Anyone with the Pl_ANALYTICS role will see the last 4 characters of the CREDICARDND column data in dear text.
Answer: A
Explanation:
* The masking policy defined in the image indicates that if a user has the PI_ANALYTICS role, they will be able to see the last 4 characters of the CREDITCARDNO column data in clear text. Otherwise, they will see 'MASKED'. Since Snowflake system roles have not been granted any additional roles, they won't have the PI_ANALYTICS role and therefore cannot view the last 4 characters of credit card numbers.
* To apply a masking policy on a column in Snowflake, you need to use the ALTER TABLE ... ALTER COLUMN command or the ALTER VIEW command and specify the policy name. For example, to apply the creditcardno_mask policy on the CREDITCARDNO column of the CREDITCARDINFO table, you can use the following command:
ALTER TABLE CREDITCARDINFO ALTER COLUMN CREDITCARDNO SET MASKING POLICY creditcardno_mask;
* For more information on how to create and use masking policies in Snowflake, you can refer to the following resources:
CREATE MASKING POLICY: This document explains the syntax and usage of the CREATE MASKING POLICY command, which allows you to create a new masking policy or replace an existing one.
Using Dynamic Data Masking: This guide provides instructions on how to configure and use dynamic data masking in Snowflake, which is a feature that allows you to mask sensitive data based on the execution context of the user.
ALTER MASKING POLICY: This document explains the syntax and usage of the ALTER MASKING POLICY command, which allows you to modify the properties of an existing masking policy.
References: 1: https://docs.snowflake.com/en/sq ... eate-masking-policy 2: https://docs.
snowflake.com/en/user-guide/security-column-ddm-use 3: https://docs.snowflake.com/en/sql-reference/sql
/alter-masking-policy

NEW QUESTION # 147
Which of the following are characteristics of Snowflake's parameter hierarchy?
  • A. Schema parameters override account parameters.
  • B. Virtual warehouse parameters override user parameters.
  • C. Table parameters override virtual warehouse parameters.
  • D. Session parameters override virtual warehouse parameters.
Answer: A
Explanation:
This is the correct answer because it reflects the characteristics of Snowflake's parameter hierarchy. Snowflake provides three types of parameters that can be set for an account: account parameters, session parameters, and object parameters. All parameters have default values, which can be set and then overridden at different levels depending on the parameter type. The following diagram illustrates the hierarchical relationship between the different parameter types and how individual parameters can be overridden at each level1:
As shown in the diagram, schema parameters are a type of object parameters that can be set for schemas. Schema parameters can override the account parameters that are set at the account level. For example, the LOG_LEVEL parameter can be set at the account level to control the logging level for all objects in the account, but it can also be overridden at the schema level to control the logging level for specific stored procedures and UDFs in that schema2.
The other options listed are not correct because they do not reflect the characteristics of Snowflake's parameter hierarchy. Session parameters do not override virtual warehouse parameters, because virtual warehouse parameters are a type of session parameters that can be set for virtual warehouses. Virtual warehouse parameters do not override user parameters, because user parameters are a type of session parameters that can be set for users. Table parameters do not override virtual warehouse parameters, because table parameters are a type of object parameters that can be set for tables, and object parameters do not affect session parameters1.
Reference:
Snowflake Documentation: Parameters
Snowflake Documentation: Setting Log Level

NEW QUESTION # 148
Consider the following COPY command which is loading data with CSV format into a Snowflake table from an internal stage through a data transformation query.

This command results in the following error:
SQL compilation error: invalid parameter 'validation_mode'
Assuming the syntax is correct, what is the cause of this error?
  • A. The value return_all_errors of the option VALIDATION_MODE is causing a compilation error.
  • B. The VALIDATION_MODE parameter does not support COPY statements that transform data during a load.
  • C. The VALIDATION_MODE parameter does not support COPY statements with CSV file formats.
  • D. The VALIDATION_MODE parameter supports COPY statements that load data from external stages only.
Answer: B
Explanation:
* The VALIDATION_MODE parameter is used to specify the behavior of the COPY statement when loading data into a table. It is used to specify whether the COPY statement should return an error if any of the rows in the file are invalid or if it should continue loading the valid rows. The VALIDATION_MODE parameter is only supported for COPY statements that load data from external stages1.
* The query in the question uses a data transformation query to load data from an internal stage. A data transformation query is a query that transforms the data during the load process, such as parsing JSON or XML data, applying functions, or joining with other tables2.
* According to the documentation, VALIDATION_MODE does not support COPY statements that transform data during a load. If the parameter is specified, the COPY statement returns an error1.
Therefore, option C is the correct answer.
COPY INTO <table> : Transforming Data During a Load

NEW QUESTION # 149
A company wants to deploy its Snowflake accounts inside its corporate network with no visibility on the internet. The company is using a VPN infrastructure and Virtual Desktop Infrastructure (VDI) for its Snowflake users. The company also wants to re-use the login credentials set up for the VDI to eliminate redundancy when managing logins.
What Snowflake functionality should be used to meet these requirements? (Choose two.)
  • A. Provision a unique company Tri-Secret Secure key.
  • B. Use a proxy Snowflake account outside the VPN, enabling client redirect for user logins.
  • C. Set up replication to allow users to connect from outside the company VPN.
  • D. Use private connectivity from a cloud provider.
  • E. Set up SSO for federated authentication.
Answer: D,E
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the Snowflake functionality that should be used to meet these requirements are:
* Use private connectivity from a cloud provider. This feature allows customers to connect to Snowflake from their own private network without exposing their data to the public Internet. Snowflake integrates with AWS PrivateLink, Azure Private Link, and Google Cloud Private Service Connect to offer private connectivity from customers' VPCs or VNets to Snowflake endpoints. Customers can control how traffic reaches the Snowflake endpoint and avoid the need for proxies or public IP addresses123.
* Set up SSO for federated authentication. This feature allows customers to use their existing identity provider (IdP) to authenticate users for SSO access to Snowflake. Snowflake supports most SAML
2.0-compliant vendors as an IdP, including Okta, Microsoft AD FS, Google G Suite, Microsoft Azure Active Directory, OneLogin, Ping Identity, and PingOne. By setting up SSO for federated authentication, customers can leverage their existing user credentials and profile information, and provide stronger security than username/password authentication4.
The other options are incorrect because they do not meet the requirements or are not feasible. Option A is incorrect because setting up replication does not allow users to connect from outside the company VPN.
Replication is a feature of Snowflake that enables copying databases across accounts in different regions and cloud platforms. Replication does not affect the connectivity or visibility of the accounts5. Option B is incorrect because provisioning a unique company Tri-Secret Secure key does not affect the network or authentication requirements. Tri-Secret Secure is a feature of Snowflake that 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. Tri-Secret Secure provides an additional layer of security and control over the data encryption and decryption process, but it does not enable private connectivity or SSO6. Option E is incorrect because using a proxy Snowflake account outside the VPN, enabling client redirect for user logins, is not a supported or recommended way of meeting the requirements. Client redirect is a feature of Snowflake that allows customers to connect to a different Snowflake account than the one specified in the connection string. This feature is useful for scenarios such as cross-region failover, data sharing, and account migration, but it does not provide private connectivity or SSO7. References: AWS PrivateLink & Snowflake | Snowflake Documentation, Azure Private Link & Snowflake | Snowflake Documentation, Google Cloud Private Service Connect & Snowflake | Snowflake Documentation, Overview of Federated Authentication and SSO | Snowflake Documentation, Replicating Databases Across Multiple Accounts | Snowflake Documentation, Tri-Secret Secure | Snowflake Documentation, Redirecting Client Connections | Snowflake Documentation

NEW QUESTION # 150
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