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Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Exam is a highly sought-after certification in the field of data warehousing and cloud computing. ARA-C01 exam is designed to test the expertise of professionals in the area of Snowflake architecture and provide them with the necessary accreditation to operate as a SnowPro Advanced Architect.

Snowflake ARA-C01 exam is intended for individuals who have significant experience in working with Snowflake technology, and who possess a strong understanding of the Snowflake platform, its features and capabilities, as well as the Snowflake architecture. ARA-C01 Exam Tests the candidate's knowledge of Snowflake's data warehousing, data processing, and data integration capabilities, as well as their ability to design and implement complex Snowflake solutions.

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Achieving the SnowPro Advanced Architect Certification demonstrates a high level of proficiency and expertise in designing and implementing complex data solutions with Snowflake. SnowPro Advanced Architect Certification certification can enhance an individual's career opportunities and provide a competitive edge in the rapidly growing field of cloud data management.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q74-Q79):

NEW QUESTION # 74
Secure views cannot take advantage of the internal optimizations which require access to the underlying data in the base tables for the view.

A. TRUE
B. FALSE

Answer: A

NEW QUESTION # 75
What are characteristics of the use of transactions in Snowflake? (Select TWO).

A. A transaction can be started explicitly by executing a begin transaction statement and end explicitly by executing an end transaction statement.
B. The autocommit setting can be changed inside a stored procedure.
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. Explicit transactions can contain DDL, DML, and query statements.

Answer: B,E

NEW QUESTION # 76
The IT Security team has identified that there is an ongoing credential stuffing attack on many of their organization's system.
What is the BEST way to find recent and ongoing login attempts to Snowflake?

A. Query the LOGIN_HISTORY view in the ACCOUNT_USAGE schema in the SNOWFLAKE database.
B. View the Users section in the Account tab in the Snowflake UI and review the last login column.
C. Call the LOGIN_HISTORY Information Schema table function.
D. View the History tab in the Snowflake UI and set up a filter for SQL text that contains the text
"LOGIN".

Answer: A

Explanation:
This view can be used to query login attempts by Snowflake users within the last 365 days (1 year). It provides information such as the event timestamp, the user name, the client IP, the authentication method, the success or failure status, and the error code or message if the login attempt was unsuccessful. By querying this view, the IT Security team can identify any suspicious or malicious login attempts to Snowflake and take appropriate actions to prevent credential stuffing attacks1. The other options are not the best ways to find recent and ongoing login attempts to Snowflake. Option A is incorrect because the LOGIN_HISTORY Information Schema table function only returns login events within the last 7 days, which may not be sufficient to detect credential stuffing attacks that span a longer period of time2. Option C is incorrect because the History tab in the Snowflake UI only shows the queries executed by the current user or role, not the login events of other users or roles3. Option D is incorrect because the Users section in the Account tab in the Snowflake UI only shows the last login time for each user, not the details of the login attempts or the failures.

NEW QUESTION # 77
A company has an external vendor who puts data into Google Cloud Storage. The company's Snowflake account is set up in Azure.
What would be the MOST efficient way to load data from the vendor into Snowflake?

A. Copy the data from Google Cloud Storage to Azure Blob storage using external tools and load data from Blob storage to Snowflake.
B. Create an external stage on Google Cloud Storage and use the external table to load the data into Snowflake.
C. Create a Snowflake Account in the Google Cloud Platform (GCP), ingest data into this account and use data replication to move the data from GCP to Azure.
D. Ask the vendor to create a Snowflake account, load the data into Snowflake and create a data share.

Answer: B

NEW QUESTION # 78
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. 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
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. 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;
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.
Reference:
Using the SIMULATED_DATA_SHARING_CONSUMER Session Parameter
SnowPro Advanced: Architect Exam Study Guide

NEW QUESTION # 79
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