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| Certification Vendor: | Snowflake |
|---|---|
| Exam Name: | SnowPro Advanced: Architect Certification Exam |
| Exam Number: | ARA-C01 |
| Exam Duration: | 115 minutes |
| Real Exam Qty: | 65 |
| Exam Format: | Multiple Select, Multiple Choice |
| Passing Score: | 750 / 1000 |
| Exam Price: | USD 375 |
| Certificate Validity Period: | 2 years |
| Related Certifications: | SnowPro Advanced: Data Analyst SnowPro Core SnowPro Advanced: Data Engineer |
| Available Languages: | English |
| Recommended Training: | Snowflake Documentation Snowflake Advanced Architect Learning Path |
| Exam Registration: | Pearson VUE Registration Snowflake Certification Portal |
| Sample Questions: | Snowflake ARA-C01 Sample Questions |
| Exam Way: | Online proctored or Onsite testing center |
| Pre Condition: | Recommended: SnowPro Core certification + 2+ years hands-on experience as Snowflake Architect in production environment |
| Official Syllabus URL: | https://learn.snowflake.com/en/certifications/snowpro-advanced-architect/ |
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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.
NEW QUESTION # 142
The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1) Finance and Vendor Management team members who require reporting and visualization
2) Data Science team members who require access to raw data for ML model development
3) Sales team members who require engineered and protected data for data monetization What Snowflake data modeling approaches will meet these requirements? (Choose two.)
Answer: A,E
Explanation:
To accommodate the diverse needs of different teams and use cases within a company, a flexible and multi-faceted approach to data modeling is required.
Option B: By creating a raw database for landing and persisting raw data, you ensure that the Data Science team has access to unprocessed data for machine learning model development. This aligns with the best practices of having a staging area or raw data zone in a modern data architecture where raw data is ingested before being transformed or processed for different use cases.
Option C: Having profile-specific databases means creating targeted databases that are designed to meet the specific requirements of each user profile or team within the company. For the Finance and Vendor Management teams, the data can be structured and optimized for reporting and visualization. For the Sales team, the database can include engineered and protected data that is suitable for data monetization efforts. This strategy not only aligns data with usage patterns but also helps in managing data access and security policies effectively.
NEW QUESTION # 143
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?
Answer: C
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.
References
Snowflake Documentation on Cloning Considerations1.
NEW QUESTION # 144
A company is using a Snowflake account in Azure. The account has SAML SSO set up using ADFS as a SCIM identity provider. To validate Private Link connectivity, an Architect performed the following steps:
* Confirmed Private Link URLs are working by logging in with a username/password account
* Verified DNS resolution by running nslookups against Private Link URLs
* Validated connectivity using SnowCD
* Disabled public access using a network policy set to use the company's IP address range However, the following error message is received when using SSO to log into the company account:
IP XX.XXX.XX.XX is not allowed to access snowflake. Contact your local security administrator.
What steps should the Architect take to resolve this error and ensure that the account is accessed using only Private Link? (Choose two.)
Answer: A,B
Explanation:
Explanation
The error message indicates that the IP address in the error message is not allowed to access Snowflake because it is not in the allowed list of the network policy. The network policy is a feature that allows restricting access to Snowflake based on IP addresses or ranges. To resolve this error, the Architect should take the following steps:
* Add the IP address in the error message to the allowed list in the network policy. This will allow the IP address to access Snowflake using the Private Link URLs. Alternatively, the Architect can disable the network policy if it is not required for security reasons.
* Update the configuration of the Azure AD SSO to use the Private Link URLs. This will ensure that the SSO authentication process uses the Private Link URLs instead of the public URLs. The configuration can be updated by following the steps in the Azure documentation1.
These two steps should resolve the error and ensure that the account is accessed using only Private Link. The other options are not necessary or relevant for this scenario. Altering the Azure security integration to use the Private Link URLs is not required because the security integration is used for SCIM provisioning, not for SSO authentication. Generating a new SCIM access token using system$generate_scim_access_token and saving it to Azure AD is not required because the SCIM access token is used for SCIM provisioning, not for SSO authentication. Opening a case with Snowflake Support to authorize the Private Link URLs' access to the account is not required because the authorization can be done by the account administrator using the SYSTEM$AUTHORIZE_PRIVATELINK function2.
NEW QUESTION # 145
Which Snowflake objects can be used in a data share? (Select TWO).
Answer: A,B
Explanation:
Data sharing is a feature that allows you to share selected objects in a database in your account with other Snowflake accounts. You can share the following Snowflake database objects: external tables, dynamic tables, secure views, secure materialized views, secure UDFs, and tables. However, not all of these objects can be used in a data share. A data share is a named object that encapsulates the information required to share a database. You can grant privileges on objects to a share either via a database role or directly to a share. The objects that can be granted privileges directly to a share are: standard views, secure views, secure UDFs, and tables.
Therefore, the correct answer is A and B. The other options are incorrect because they cannot be granted privileges directly to a share. External tables, dynamic tables, and streams can only be shared via a database role. Stored procedures cannot be shared at all. Reference:
[Introduction to Secure Data Sharing] 1
[Working with Shares] 2
[Choosing How to Share Database Objects] 3
NEW QUESTION # 146
An Architect needs to grant a group of ORDER_ADMIN users the ability to clean old data in an ORDERS table (deleting all records older than 5 years), without granting any privileges on the table. The group's manager (ORDER_MANAGER) has full DELETE privileges on the table.
How can the ORDER_ADMIN role be enabled to perform this data cleanup, without needing the DELETE privilege held by the ORDER_MANAGER role?
Answer: A
Explanation:
This is the correct answer because it allows the ORDER_ADMIN role to perform the data cleanup without needing the DELETE privilege on the ORDERS table. A stored procedure is a feature that allows scheduling and executing SQL statements or stored procedures in Snowflake. A stored procedure can run with either the caller's rights or the owner's rights. A caller's rights stored procedure runs with the privileges of the role that called the stored procedure, while an owner's rights stored procedure runs with the privileges of the role that created the stored procedure. By creating a stored procedure that runs with owner's rights, the ORDER_MANAGER role can delegate the specific task of deleting old data to the ORDER_ADMIN role, without granting the ORDER_ADMIN role more general privileges on the ORDERS table. The stored procedure must include the appropriate business logic to delete only the records older than 5 years, and the ORDER_MANAGER role must grant the USAGE privilege on the stored procedure to the ORDER_ADMIN role. The ORDER_ADMIN role can then execute the stored procedure to perform the data cleanup12.
Snowflake Documentation: Stored Procedures
Snowflake Documentation: Understanding Caller's Rights and Owner's Rights Stored Procedures
NEW QUESTION # 147
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