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Snowflake ARA-C01 Exam is a certification exam designed for advanced architects who are experienced in implementing and operating Snowflake solutions. ARA-C01 exam is the highest level of certification offered by Snowflake and is intended to validate the skills and expertise of professionals who are responsible for designing, building, and managing complex Snowflake environments.

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Snowflake ARA-C01 Exam is a challenging and rigorous certification that is designed to recognize the top architects in the Snowflake community. By earning this certification, professionals can demonstrate their ability to design and manage complex Snowflake environments, and position themselves as leaders in this fast-growing field.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q15-Q20):

NEW QUESTION # 15
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.)

A. Open a case with Snowflake Support to authorize the Private Link URLs' access to the account.
B. Alter the Azure security integration to use the Private Link URLs.
C. Update the configuration of the Azure AD SSO to use the Private Link URLs.
D. Generate a new SCIM access token using system$generate_scim_access_token and save it to Azure AD.
E. Add the IP address in the error message to the allowed list in the network policy.

Answer: C,E

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 # 16
What does a Snowflake Architect need to consider when implementing a Snowflake Connector for Kafka?

A. The Kafka connector will create one table and one pipe to ingest data for each topic. If the connector cannot create the table or the pipe it will result in an exception.
B. The default retention time for Kafka topics is 14 days.
C. The Kafka connector supports key pair authentication, OAUTH. and basic authentication (for example, username and password).
D. Every Kafka message is in JSON or Avro format.

Answer: B

NEW QUESTION # 17
A data platform team creates two multi-cluster virtual warehouses with the AUTO_SUSPEND value set to NULL on one. and '0' on the other. What would be the execution behavior of these virtual warehouses?

A. Setting a '0' or NULL value means the warehouses will never suspend.
B. Setting a '0' value means the warehouses will suspend immediately, and NULL means the warehouses will never suspend.
C. Setting a '0' or NULL value means the warehouses will suspend immediately.
D. Setting a '0' or NULL value means the warehouses will suspend after the default of 600 seconds.

Answer: B

Explanation:
The AUTO_SUSPEND parameter controls the amount of time, in seconds, of inactivity after which a warehouse is automatically suspended. If the parameter is set to NULL, the warehouse never suspends. If the parameter is set to '0', the warehouse suspends immediately after executing a query. Therefore, the execution behavior of the two virtual warehouses will be different depending on the AUTO_SUSPEND value. The warehouse with NULL value will keep running until it is manually suspended or the resource monitor limits are reached. The warehouse with '0' value will suspend as soon as it finishes a query and release the compute resources. Reference:
ALTER WAREHOUSE
Parameters

NEW QUESTION # 18
Which of the below query will you run to get the approximate number of distinct values in a table?

A. select approx_count(column1) from table1;
B. select approx_count_distinct(column1) from table1;
C. select count_distinct(column1 approx) from table1;

Answer: B

NEW QUESTION # 19
What Snowflake features should be leveraged when modeling using Data Vault?

A. Snowflake's support of multi-table inserts into the data model's Data Vault tables
B. Snowflake's ability to hash keys so that hash key joins can run faster than integer joins
C. Scaling up the virtual warehouses will support parallel processing of new source loads
D. Data needs to be pre-partitioned to obtain a superior data access performance

Answer: A,C

Explanation:
Explanation
These two features are relevant for modeling using Data Vault on Snowflake. Data Vault is a data modeling approach that organizes data into hubs, links, and satellites. Data Vault is designed to enable high scalability, flexibility, and performance for data integration and analytics. Snowflake is a cloud data platform that supports various data modeling techniques, including Data Vault. Snowflake provides some features that can enhance the Data Vault modeling, such as:
* Snowflake's support of multi-table inserts into the data model's Data Vault tables. Multi-table inserts (MTI) are a feature that allows inserting data from a single query into multiple tables in a single DML statement. MTI can improve the performance and efficiency of loading datainto Data Vault tables, especially for real-time or near-real-time data integration. MTI can also reduce the complexity and maintenance of the loading code, as well as the data duplication and latency12.
* Scaling up the virtual warehouses will support parallel processing of new source loads. Virtual warehouses are a feature that allows provisioning compute resources on demand for data processing.
Virtual warehouses can be scaled up or down by changing the size of the warehouse, which determines the number of servers in the warehouse. Scaling up the virtual warehouses can improve the performance and concurrency of processing new source loads into Data Vault tables, especially for large or complex data sets. Scaling up the virtual warehouses can also leverage the parallelism and distribution of Snowflake's architecture, which can optimize the data loading and querying34.
References:
* Snowflake Documentation: Multi-table Inserts
* Snowflake Blog: Tips for Optimizing the Data Vault Architecture on Snowflake
* Snowflake Documentation: Virtual Warehouses
* Snowflake Blog: Building a Real-Time Data Vault in Snowflake

NEW QUESTION # 20
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