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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 (Q154-Q159):

NEW QUESTION # 154
When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)

A. Avro
B. XML
C. Parquet
D. JSON
E. CSV

Answer: A,D

Explanation:
Explanation
The data formats that are supported for the messages when using the Snowflake Connector for Kafka are Avro and JSON. These are the two formats that the connector can parse and convert into Snowflake table rows. The connector supports both schemaless and schematized JSON, as well as Avro with or without a schema registry1. The other options are incorrect because they are not supported data formats for the messages. CSV, XML, and Parquet are not formats that the connector can parse and convert into Snowflake table rows. If the messages are in these formats, the connector will load them as VARIANT data type and store them as raw strings in the table2. References: Snowflake Connector for Kafka | Snowflake Documentation, Loading Protobuf Data using the Snowflake Connector for Kafka | Snowflake Documentation

NEW QUESTION # 155
Which of the following are characteristics of Snowflake's parameter hierarchy?

A. Session parameters override virtual warehouse parameters.
B. Virtual warehouse parameters override user parameters.
C. Table parameters override virtual warehouse parameters.
D. Schema parameters override account parameters.

Answer: D

Explanation:
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.
References:
* Snowflake Documentation: Parameters
* Snowflake Documentation: Setting Log Level

NEW QUESTION # 156
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. 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;
C. 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
D. 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*

Answer: D

Explanation:
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.
References:
* Using the SIMULATED_DATA_SHARING_CONSUMER Session Parameter
* SnowPro Advanced: Architect Exam Study Guide

NEW QUESTION # 157
Which security, governance, and data protection features require, at a MINIMUM, the Business Critical edition of Snowflake? (Choose two.)

A. Customer-managed encryption keys through Tri-Secret Secure
B. AWS, Azure, or Google Cloud private connectivity to Snowflake
C. Federated authentication and SSO
D. Periodic rekeying of encrypted data
E. Extended Time Travel (up to 90 days)

Answer: A,B

NEW QUESTION # 158
What are characteristics of the use of transactions in Snowflake? (Select TWO).

A. Explicit transactions can contain DDL, DML, and query statements.
B. A transaction can be started explicitly by executing a begin transaction statement and end explicitly by executing an end transaction statement.
C. Explicit transactions should contain only DML statements and query statements. All DDL statements implicitly commit active transactions.
D. A transaction can be started explicitly by executing a begin work statement and end explicitly by executing a commit work statement.
E. The autocommit setting can be changed inside a stored procedure.

Answer: A,D

Explanation:
A: Snowflake's transactions can indeed include DDL (Data Definition Language), DML (Data Manipulation Language), and query statements. When executed within a transaction block, they all contribute to the atomicity of the transaction-either all of them commit together or none at all.C. Snowflake supports explicit transaction control through the use of the BEGIN TRANSACTION (or simply BEGIN) and COMMIT statements. Alternatively, the BEGIN WORK and COMMIT WORK syntax is also supported, which is a standard SQL syntax for initiating and ending transactions, respectively.Note: The END TRANSACTION statement is not used in Snowflake to end a transaction; the correct statement is COMMIT or COMMIT WORK.

NEW QUESTION # 159
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