[Aug-2026] Check your preparation for Snowflake ARA-C01 On-Demand Exam [Q87-Q111]

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[Aug-2026] Check your preparation for Snowflake ARA-C01 On-Demand Exam

Practice Exam ARA-C01 Realistic Dumps Verified Questions

In order to prepare for the SnowPro Advanced Architect Certification exam, candidates can take advantage of various resources provided by Snowflake, such as training courses, study guides, and practice exams. Additionally, candidates can also benefit from hands-on experience working with Snowflake’s cloud data platform, as well as collaborating with other Snowflake experts and architects.

Snowflake ARA-C01 certification exam is a vendor-neutral certification, which means that it is recognized across the industry, regardless of the specific technology or solution being used. SnowPro Advanced Architect Certification certification is intended for professionals who have a deep understanding of Snowflake architecture and its various components, including data integration, data warehousing, data modeling, and data governance.

Q87. What are characteristics of the use of transactions in Snowflake? (Select TWO).

Explicit transactions can contain DDL, DML, and query statements.

The autocommit setting can be changed inside a stored procedure.

A transaction can be started explicitly by executing a begin work statement and end explicitly by executing a commit work statement.

A transaction can be started explicitly by executing a begin transaction statement and end explicitly by executing an end transaction statement.

Explicit transactions should contain only DML statements and query statements. All DDL statements implicitly commit active transactions.

Q88. How can the Snowpipe REST API be used to keep a log of data load history?

Call insertReport every 20 minutes, fetching the last 10,000 entries.

Call loadHistoryScan every minute for the maximum time range.

Call insertReport every 8 minutes for a 10-minute time range.

Call loadHistoryScan every 10 minutes for a 15-minute time range.

Q89. When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)

CSV

XML

Avro

JSON

Parquet

Q90. An Architect needs to allow a user to create a database from an inbound share.
To meet this requirement, the user’s role must have which privileges? (Choose two.)

IMPORT SHARE;

IMPORT PRIVILEGES;

CREATE DATABASE;

CREATE SHARE;

IMPORT DATABASE;

Q91. Based on the Snowflake object hierarchy, what securable objects belong directly to a Snowflake account?
(Select THREE).

Database

Schema

Table

Stage

Role

Warehouse

Q92. Based on the Snowflake object hierarchy, what securable objects belong directly to a Snowflake account?
(Select THREE).

Database

Schema

Table

Stage

Role

Warehouse

Q93. 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?

Create a stored procedure that runs with caller’s rights, including the appropriate “> 5 years” business logic, and grant USAGE on this procedure to ORDER_ADMIN. The ORDER_MANAGER role owns the procedure.

Create a stored procedure that can be run using both caller’s and owner’s rights (allowing the user to specify which rights are used during execution), and grant USAGE on this procedure to ORDER_ADMIN. The ORDER_MANAGER role owns the procedure.

Create a stored procedure that runs with owner’s rights, including the appropriate “> 5 years” business logic, and grant USAGE on this procedure to ORDER_ADMIN. The ORDER_MANAGER role owns the procedure.

This scenario would actually not be possible in Snowflake – any user performing a DELETE on a table requires the DELETE privilege to be granted to the role they are using.

Q94. A retailer’s enterprise data organization is exploring the use of Data Vault 2.0 to model its data lake solution.
A Snowflake Architect has been asked to provide recommendations for using Data Vault 2.0 on Snowflake.
What should the Architect tell the data organization? (Select TWO).

Change data capture can be performed using the Data Vault 2.0 HASH_DIFF concept.

Change data capture can be performed using the Data Vault 2.0 HASH_DELTA concept.

Using the multi-table insert feature in Snowflake, multiple Point-in-Time (PIT) tables can be loaded in parallel from a single join query from the data vault.

Using the multi-table insert feature, multiple Point-in-Time (PIT) tables can be loaded sequentially from a single join query from the data vault.

There are performance challenges when using Snowflake to load multiple Point-in-Time (PIT) tables in parallel from a single join query from the data vault.

Q95. One of your joins is taking a lot of time. The query profile view looks like this.
What may be the issue?

This may be an “exploding join” issue. The query has provided a condition where records from one table match multiple records from another table resulting in a cartesian product

There is not enough memory to process the join query

Looks like tablescan is the most expensive operation in the profile.

Q96. What are purposes for creating a storage integration? (Choose three.)

Control access to Snowflake data using a master encryption key that is maintained in the cloud provider’s key management service.

Store a generated identity and access management (IAM) entity for an external cloud provider regardless of the cloud provider that hosts the Snowflake account.

Support multiple external stages using one single Snowflake object.

Avoid supplying credentials when creating a stage or when loading or unloading data.

Create private VPC endpoints that allow direct, secure connectivity between VPCs without traversing the public internet.

Manage credentials from multiple cloud providers in one single Snowflake object.

Q97. A company has a table with that has corrupted data, named Data. The company wants to recover the data as it was 5 minutes ago using cloning and Time Travel.
What command will accomplish this?

CREATE CLONE TABLE Recover_Data FROM Data AT(OFFSET => -60*5);

CREATE CLONE Recover_Data FROM Data AT(OFFSET => -60*5);

CREATE TABLE Recover_Data CLONE Data AT(OFFSET => -60*5);

CREATE TABLE Recover Data CLONE Data AT(TIME => -60*5);

Q98. A new user user_01 is created within Snowflake. The following two commands are executed:
Command 1# SHOW GRANTS TO USER user_01;
Command 2# SHOW GRANTS ON USER user_01;
What inferences can be made about these commands?

Command 1 defines which user owns user_01Command 2 defines all the grants which have been given to user_01

Command 1 defines all the grants which are given to user_01Command 2 defines which user owns user_01

Command 1 defines which role owns user_01Command 2 defines all the grants which have been given to user_01

Command 1 defines all the grants which are given to user_01Command 2 defines which role owns user_01

Q99. A call center processes sensitive PII and PHI data. Requirements:
* Object owners and privileged roles must see sensitive columns.
* Pre-tokenized data must be de-tokenized at query time.What should be used? (Select TWO).

Object tagging

Materialized views

External tokenization

Dynamic Data Masking

Role-Based Access Control (RBAC)

Q100. A retail company has over 3000 stores all using the same Point of Sale (POS) system. The company wants to deliver near real-time sales results to category managers. The stores operate in a variety of time zones and exhibit a dynamic range of transactions each minute, with some stores having higher sales volumes than others.
Sales results are provided in a uniform fashion using data engineered fields that will be calculated in a complex data pipeline. Calculations include exceptions, aggregations, and scoring using external functions interfaced to scoring algorithms. The source data for aggregations has over 100M rows.
Every minute, the POS sends all sales transactions files to a cloud storage location with a naming convention that includes store numbers and timestamps to identify the set of transactions contained in the files. The files are typically less than 10MB in size.
How can the near real-time results be provided to the category managers? (Select TWO).

All files should be concatenated before ingestion into Snowflake to avoid micro-ingestion.

A Snowpipe should be created and configured with AUTO_INGEST = true. A stream should be created to process INSERTS into a single target table using the stream metadata to inform the store number and timestamps.

A stream should be created to accumulate the near real-time data and a task should be created that runs at a frequency that matches the real-time analytics needs.

An external scheduler should examine the contents of the cloud storage location and issue SnowSQL commands to process the data at a frequency that matches the real-time analytics needs.

The copy into command with a task scheduled to run every second should be used to achieve the near-real time requirement.

Q101. Company A has recently acquired company B. The Snowflake deployment for company B is located in the Azure West Europe region.
As part of the integration process, an Architect has been asked to consolidate company B’s sales data into company A’s Snowflake account which is located in the AWS us-east-1 region.
How can this requirement be met?

Replicate the sales data from company B’s Snowflake account into company A’s Snowflake account using cross-region data replication within Snowflake. Configure a direct share from company B’s account to company A’s account.

Export the sales data from company B’s Snowflake account as CSV files, and transfer the files to company A’s Snowflake account. Import the data using Snowflake’s data loading capabilities.

Migrate company B’s Snowflake deployment to the same region as company A’s Snowflake deployment, ensuring data locality. Then perform a direct database-to-database merge of the sales data.

Build a custom data pipeline using Azure Data Factory or a similar tool to extract the sales data from company B’s Snowflake account. Transform the data, then load it into company A’s Snowflake account.

Q102. An Architect runs the following SQL query:

How can this query be interpreted?

FILEROWS is a stage. FILE_ROW_NUMBER is line number in file.

FILEROWS is the table. FILE_ROW_NUMBER is the line number in the table.

FILEROWS is a file. FILE_ROW_NUMBER is the file format location.

FILERONS is the file format location. FILE_ROW_NUMBER is a stage.

Q103. When loading data from stage using COPY INTO, what options can you specify for the ON_ERROR clause?

CONTINUE

SKIP_FILE

ABORT_STATEMENT

FAIL

Q104. What built-in Snowflake features make use of the change tracking metadata for a table? (Choose two.)

The MERGE command

The UPSERT command

The CHANGES clause

A STREAM object

The CHANGE_DATA_CAPTURE command

Q105. How can the Snowpipe REST API be used to keep a log of data load history?

Call insertReport every 20 minutes, fetching the last 10,000 entries.

Call loadHistoryScan every minute for the maximum time range.

Call insertReport every 8 minutes for a 10-minute time range.

Call loadHistoryScan every 10 minutes for a 15-minute time range.

Q106. Select the true statement

Privileges are granted to roles. Roles are granted to users

Privileges are granted to users. Users are granted to roles

Privileges are granted to both roles and users

Q107. Which data models can be used when modeling tables in a Snowflake environment? (Select THREE).

Graph model

Dimensional/Kimball

Data lake

lnmon/3NF

Bayesian hierarchical model

Data vault

Q108. What is a valid object hierarchy when building a Snowflake environment?

Account –> Database –> Schema –> Warehouse

Organization –> Account –> Database –> Schema –> Stage

Account –> Schema > Table –> Stage

Organization –> Account –> Stage –> Table –> View

Explanation
This is the valid object hierarchy when building a Snowflake environment, according to the Snowflake documentation and the web search results. Snowflake is a cloud data platform that supports various types of objects, such as databases, schemas, tables, views, stages, warehouses, and more. These objects are organized in a hierarchical structure, as follows:
* Organization: An organization is the top-level entity that represents a group of Snowflake accounts that are related by business needs or ownership. An organization can have one or more accounts, and can enable features such as cross-account data sharing, billing and usage reporting, and single sign-on across accounts12.
* Account: An account is the primary entity that represents a Snowflake customer. An account can have one or more databases, schemas, stages, warehouses, and other objects. An account can also have one or more users, roles, and security integrations. An account is associated with a specific cloud platform, region, and Snowflake edition34.
* Database: A database is a logical grouping of schemas. A database can have one or more schemas, and can store structured, semi-structured, or unstructured data. A database can also have properties such as retention time, encryption, and ownership56.
* Schema: A schema is a logical grouping of tables, views, stages, and other objects. A schema can have one or more objects, and can define the namespace and access control for the objects. A schema can also have properties such as ownership and default warehouse .
* Stage: A stage is a named location that references the files in external or internal storage. A stage can be used to load data into Snowflake tables using the COPY INTO command, or to unload data from Snowflake tables using the COPY INTO LOCATION command. A stage can be created at the account, database, or schema level, and can have properties such as file format, encryption, and credentials .
The other options listed are not valid object hierarchies, because they either omit or misplace some objects in the structure. For example, option A omits the organization level and places the warehouse under the schema level, which is incorrect. Option C omits the organization, account, and stage levels, and places the table under the schema level, which is incorrect. Option D omits the database level and places the stage and table under the account level, which is incorrect.
References:
* Snowflake Documentation: Organizations
* Snowflake Blog: Introducing Organizations in Snowflake
* Snowflake Documentation: Accounts
* Snowflake Blog: Understanding Snowflake Account Structures
* Snowflake Documentation: Databases
* Snowflake Blog: How to Create a Database in Snowflake
* [Snowflake Documentation: Schemas]
* [Snowflake Blog: How to Create a Schema in Snowflake]
* [Snowflake Documentation: Stages]
* [Snowflake Blog: How to Use Stages in Snowflake]

Q109. While choosing a cluster key, what is recommended by snowflake?

Cluster columns that are most actively used in selective filters

If there is room for additional cluster keys, then consider columns frequently used in join predicates

Choose a key with high cardinality

Q110. Which steps are recommended best practices for prioritizing cluster keys in Snowflake? (Choose two.)

Choose columns that are frequently used in join predicates.

Choose lower cardinality columns to support clustering keys and cost effectiveness.

Choose TIMESTAMP columns with nanoseconds for the highest number of unique rows.

Choose cluster columns that are most actively used in selective filters.

Choose cluster columns that are actively used in the GROUP BY clauses.

Q111. How can the Snowflake context functions be used to help determine whether a user is authorized to see data that has column-level security enforced? (Select TWO).

Set masking policy conditions using current_role targeting the role in use for the current session.

Set masking policy conditions using is_role_in_session targeting the role in use for the current account.

Set masking policy conditions using invoker_role targeting the executing role in a SQL statement.

Determine if there are ownership privileges on the masking policy that would allow the use of any function.

Assign the accountadmin role to the user who is executing the object.

Snowflake context functions are functions that return information about the current session, user, role, warehouse, database, schema, or object. They can be used to help determine whether a user is authorized to see data that has column-level security enforced by setting masking policy conditions based on the context functions. The following context functions are relevant for column-level security:
* current_role: This function returns the name of the role in use for the current session. It can be used to set masking policy conditions that target the current session and are not affected by the execution context of the SQL statement. For example, a masking policy condition using current_role can allow or deny access to a column based on the role that the user activated in the session.
* invoker_role: This function returns the name of the executing role in a SQL statement. It can be used to set masking policy conditions that target the executing role and are affected by the execution context of the SQL statement. For example, a masking policy condition using invoker_role can allow or deny access to a column based on the role that the user specified in the SQL statement, such as using the AS ROLE clause or a stored procedure.
* is_role_in_session: This function returns TRUE if the user’s current role in the session (i.e. the role returned by current_role) inherits the privileges of the specified role. It can be used to set masking policy conditions that involve role hierarchy and privilege inheritance. For example, a masking policy condition using is_role_in_session can allow or deny access to a column based on whether the user’s current role is a lower privilege role in the specified role hierarchy.
The other options are not valid ways to use the Snowflake context functions for column-level security:
* Set masking policy conditions using is_role_in_session targeting the role in use for the current account.
This option is incorrect because is_role_in_session does not target the role in use for the current account,
* but rather the role in use for the current session. Also, the current account is not a role, but rather a logical entity that contains users, roles, warehouses, databases, and other objects.
* Determine if there are ownership privileges on the masking policy that would allow the use of any function. This option is incorrect because ownership privileges on the masking policy do not affect the use of any function, but rather the ability to create, alter, or drop the masking policy. Also, this is not a way to use the Snowflake context functions, but rather a way to check the privileges on the masking policy object.
* Assign the accountadmin role to the user who is executing the object. This option is incorrect because assigning the accountadmin role to the user who is executing the object does not involve using the Snowflake context functions, but rather granting the highest-level role to the user. Also, this is not a recommended practice for column-level security, as it would give the user full access to all objects and data in the account, which could compromise data security and governance.
References:
* Context Functions
* Advanced Column-level Security topics
* Snowflake Data Governance: Column Level Security Overview
* Data Security Snowflake Part 2 – Column Level Security