Pass Snowflake ARA-C01 Actual Free Exam Q&As Updated Dump Aug 14, 2025 [Q81-Q95]

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Pass Snowflake ARA-C01 Actual Free Exam Q&As Updated Dump Aug 14, 2025

Latest ARA-C01 Actual Free Exam Updated 164 Questions

Snowflake ARA-C01 exam is a challenging test that requires the candidate to have a deep understanding of Snowflake’s cloud data platform and its various components. ARA-C01 exam tests the candidate’s ability to design and implement solutions that are scalable, high-performance, and cost-effective.

Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Certification Exam is an essential credential for professionals who want to demonstrate their expertise in Snowflake architecture. SnowPro Advanced Architect Certification certification program is designed to help professionals stay up-to-date with the latest industry trends and technologies, and it can help them advance their careers by demonstrating their skills and knowledge to potential employers.

NEW QUESTION 81
Following objects can be cloned in snowflake

Permanent table

Transient table

Temporary table

External tables

Internal stages

NEW QUESTION 82
An Architect has a VPN_ACCESS_LOGS table in the SECURITY_LOGS schema containing timestamps of the connection and disconnection, username of the user, and summary statistics.
What should the Architect do to enable the Snowflake search optimization service on this table?

Assume role with OWNERSHIP on future tables and ADD SEARCH OPTIMIZATION on the SECURITY_LOGS schema.

Assume role with ALL PRIVILEGES including ADD SEARCH OPTIMIZATION in the SECURITY LOGS schema.

Assume role with OWNERSHIP on VPN_ACCESS_LOGS and ADD SEARCH OPTIMIZATION in the SECURITY_LOGS schema.

Assume role with ALL PRIVILEGES on VPN_ACCESS_LOGS and ADD SEARCHOPTIMIZATION in the SECURITY_LOGS schema.

NEW QUESTION 83
The following table exists in the production database:
A regulatory requirement states that the company must mask the username for events that are older than six months based on the current date when the data is queried.
How can the requirement be met without duplicating the event data and making sure it is applied when creating views using the table or cloning the table?

Use a masking policy on the username column using a entitlement table with valid dates.

Use a row level policy on the user_events table using a entitlement table with valid dates.

Use a masking policy on the username column with event_timestamp as a conditional column.

Use a secure view on the user_events table using a case statement on the username column.

A masking policy is a feature of Snowflake that allows masking sensitive data in query results based on the role of the user and the condition of the data. A masking policy can be applied to a column in a table or a view, and it can use another column in the same table or view as a conditional column. A conditional column is a column that determines whether the masking policy is applied or not based on its value1.
In this case, the requirement can be met by using a masking policy on the username column with event_timestamp as a conditional column. The masking policy can use a function that masks the username if the event_timestamp is older than six months based on the current date, and returns the original username otherwise. The masking policy can be applied to the user_events table, and it will also be applied when creating views using the table or cloning the table2.
The other options are not correct because:
* A. Using a masking policy on the username column using an entitlement table with valid dates would require creating another table that stores the valid dates for each username, and joining it with the user_events table in the masking policy function. This would add complexity and overhead to the masking policy, and it would not use the event_timestamp column as the condition for masking.
* B. Using a row level policy on the user_events table using an entitlement table with valid dates would require creating another table that stores the valid dates for each username, and joining it with the user_events table in the row access policy function. This would filter out the rows that have event_timestamp older than six months based on the valid dates, instead of masking the username column. This would not meet the requirement of masking the username, and it would also reduce the visibility of the event data.
* D. Using a secure view on the user_events table using a case statement on the username column would require creating a view that uses a case expression to mask the username column based on the event_timestamp column. This would meet the requirement of masking the username, but it would not be applied when cloning the table. A secure view is a view that prevents the underlying data from being exposed by queries on the view. However, a secure view does not prevent the underlying data from being exposed by cloning the table3.
References:
* 1: Masking Policies | Snowflake Documentation
* 2: Using Conditional Columns in Masking Policies | Snowflake Documentation
* 3: Secure Views | Snowflake Documentation

NEW QUESTION 84
A user named USER_01 needs access to create a materialized view on a schema EDW. STG_SCHEMA. How can this access be provided?

GRANT CREATE MATERIALIZED VIEW ON SCHEMA EDW.STG_SCHEMA TO USER
USER_01;

GRANT CREATE MATERIALIZED VIEW ON DATABASE EDW TO USER USERJD1;

GRANT ROLE NEW_ROLE TO USER USER_01;GRANT CREATE MATERIALIZED VIEW ON SCHEMA ECW.STG_SCHEKA TO NEW_ROLE;

GRANT ROLE NEW_ROLE TO USER_01;GRANT CREATE MATERIALIZED VIEW ON EDW.STG_SCHEMA TO NEW_ROLE;

NEW QUESTION 85
Following objects can be cloned in snowflake

Permanent table

Transient table

Temporary table

External tables

Internal stages

NEW QUESTION 86
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?

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;

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;

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*

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

NEW QUESTION 87
Which feature provides the capability to define an alternate cluster key for a table with an existing cluster key?

External table

Materialized view

Search optimization

Result cache

NEW QUESTION 88
An Architect needs to improve the performance of reports that pull data from multiple Snowflake tables, join, and then aggregate the data. Users access the reports using several dashboards. There are performance issues on Monday mornings between 9:00am-11:00am when many users check the sales reports.
The size of the group has increased from 4 to 8 users. Waiting times to refresh the dashboards has increased significantly. Currently this workload is being served by a virtual warehouse with the following parameters:
AUTO-RESUME = TRUE AUTO_SUSPEND = 60 SIZE = Medium
What is the MOST cost-effective way to increase the availability of the reports?

Use materialized views and pre-calculate the data.

Increase the warehouse to size Large and set auto_suspend = 600.

Use a multi-cluster warehouse in maximized mode with 2 size Medium clusters.

Use a multi-cluster warehouse in auto-scale mode with 1 size Medium cluster, and set min_cluster_count = 1 and max_cluster_count = 4.

NEW QUESTION 89
An Architect needs to design a data unloading strategy for Snowflake, that will be used with the COPY INTO
<location> command.
Which configuration is valid?

Location of files: Snowflake internal location
. File formats: CSV, XML
. File encoding: UTF-8
. Encryption: 128-bit

Location of files: Amazon S3
. File formats: CSV, JSON
. File encoding: Latin-1 (ISO-8859)
. Encryption: 128-bit

Location of files: Google Cloud Storage
. File formats: Parquet
. File encoding: UTF-8
Compression: gzip

Location of files: Azure ADLS
. File formats: JSON, XML, Avro, Parquet, ORC
. Compression: bzip2
. Encryption: User-supplied key

NEW QUESTION 90
A company is using Snowflake in Azure in the Netherlands. The company analyst team also has data in JSON format that is stored in an Amazon S3 bucket in the AWS Singapore region that the team wants to analyze.
The Architect has been given the following requirements:
1. Provide access to frequently changing data
2. Keep egress costs to a minimum
3. Maintain low latency
How can these requirements be met with the LEAST amount of operational overhead?

Use a materialized view on top of an external table against the S3 bucket in AWS Singapore.

Use an external table against the S3 bucket in AWS Singapore and copy the data into transient tables.

Copy the data between providers from S3 to Azure Blob storage to collocate, then use Snowpipe for data ingestion.

Use AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then use an external table against the Blob storage.

Option A is the best design to meet the requirements because it uses a materialized view on top of an external table against the S3 bucket in AWS Singapore. A materialized view is a database object that contains the results of a query and can be refreshed periodically to reflect changes in the underlying data1. An external table is a table that references data files stored in a cloud storage service, such as Amazon S32. By using a materialized view on top of an external table, the company can provide access to frequently changing data, keep egress costs to a minimum, and maintain low latency. This is because the materialized view will cache the query results in Snowflake, reducing the need to access the external data files and incur network charges.
The materialized view will also improve the query performance by avoiding scanning the external data files every time. The materialized view can be refreshed on a schedule or on demand to capture the changes in the external data files1.
Option B is not the best design because it uses an external table against the S3 bucket in AWS Singapore and copies the data into transient tables. A transient table is a table that is not subject to the Time Travel and Fail-safe features of Snowflake, and is automatically purged after a period of time3. By using an external table and copying the data into transient tables, the company will incur more egress costs and operational overhead than using a materialized view. This is because the external table will access the external data files every time a query is executed, and the copy operation will also transfer data from S3 to Snowflake. The transient tables will also consume more storage space in Snowflake and require manual maintenance to ensure they are up to date.
Option C is not the best design because it copies the data between providers from S3 to Azure Blob storage to collocate, then uses Snowpipe for data ingestion. Snowpipe is a service that automates the loading of data from external sources into Snowflake tables4. By copying the data between providers, the company will incur high egress costs and latency, as well as operational complexity and maintenance of the infrastructure. Snowpipe will also add another layer of processing and storage in Snowflake, which may not be necessary if the external data files are already in a queryable format.
Option D is not the best design because it uses AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then uses an external table against the Blob storage. AWS Transfer Family is a service that enables secure and seamless transfer of files over SFTP, FTPS, and FTP to and from Amazon S3 or Amazon EFS5. By using AWS Transfer Family, the company will incur high egress costs and latency, as well as operational complexity and maintenance of the infrastructure. The external table will also access the external data files every time a query is executed, which may affect the query performance.
References: 1: Materialized Views 2: External Tables 3: Transient Tables 4: Snowpipe Overview 5: AWS Transfer Family

NEW QUESTION 91
Database DB1 has schema S1 which has one table, T1.
DB1 –> S1 –> T1
The retention period of EG1 is set to 10 days.
The retention period of s: is set to 20 days.
The retention period of t: Is set to 30 days.
The user runs the following command:
Drop Database DB1;
What will the Time Travel retention period be for T1?

10 days

20 days

30 days

37 days

NEW QUESTION 92
Which Snowflake data modeling approach is designed for BI queries?

3 NF

Star schema

Data Vault

Snowflake schema

NEW QUESTION 93
How do Snowflake databases that are created from shares differ from standard databases that are not created from shares? (Choose three.)

Shared databases are read-only.

Shared databases must be refreshed in order for new data to be visible.

Shared databases cannot be cloned.

Shared databases are not supported by Time Travel.

Shared databases will have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share.

Shared databases can also be created as transient databases.

According to the SnowPro Advanced: Architect documents and learning resources, the ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares are:
Shared databases are read-only. This means that the data consumers who access the shared databases cannot modify or delete the data or the objects in the databases. The data providers who share the databases have full control over the data and the objects, and can grant or revoke privileges on them1.
Shared databases cannot be cloned. This means that the data consumers who access the shared databases cannot create a copy of the databases or the objects in the databases. The data providers who share the databases can clone the databases or the objects, but the clones are not automatically shared2.
Shared databases are not supported by Time Travel. This means that the data consumers who access the shared databases cannot use the AS OF clause to query historical data or restore deleted data. The data providers who share the databases can use Time Travel on the databases or the objects, but the historical data is not visible to the data consumers3.
The other options are incorrect because they are not ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares. Option B is incorrect because shared databases do not need to be refreshed in order for new data to be visible. The data consumers who access the shared databases can see the latest data as soon as the data providers update the data1. Option E is incorrect because shared databases will not have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share. The data consumers who access the shared databases can only see the objects that the data providers grant to the share, and the PUBLIC and INFORMATION_SCHEMA schemas are not granted by default4. Option F is incorrect because shared databases cannot be created as transient databases. Transient databases are databases that do not support Time Travel or Fail-safe, and can be dropped without affecting the retention period of the data. Shared databases are always created as permanent databases, regardless of the type of the source database5. Reference: Introduction to Secure Data Sharing | Snowflake Documentation, Cloning Objects | Snowflake Documentation, Time Travel | Snowflake Documentation, Working with Shares | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation

NEW QUESTION 94
Which of the below commands will use warehouse credits?

SHOW TABLES LIKE ‘SNOWFL%’;

SELECT MAX(FLAKE_ID) FROM SNOWFLAKE;

SELECT COUNT(*) FROM SNOWFLAKE;

SELECT COUNT(FLAKE_ID) FROM SNOWFLAKE GROUP BY FLAKE_ID;

NEW QUESTION 95
A retail company has 2000+ stores spread across the country. Store Managers report that they are having trouble running key reports related to inventory management, sales targets, payroll, and staffing during business hours. The Managers report that performance is poor and time-outs occur frequently.
Currently all reports share the same Snowflake virtual warehouse.
How should this situation be addressed? (Select TWO).

Use a Business Intelligence tool for in-memory computation to improve performance.

Configure a dedicated virtual warehouse for the Store Manager team.

Configure the virtual warehouse to be multi-clustered.

Configure the virtual warehouse to size 4-XL

Advise the Store Manager team to defer report execution to off-business hours.

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Pass Snowflake ARA-C01 Actual Free Exam Q&As Updated Dump Aug 14, 2025 [Q81-Q95]

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