163 Q&As in UPDATED ARA-C01 Exam Questions Certification Test Engine to PDF [Q41-Q61]

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163 Q&As in UPDATED ARA-C01 Exam Questions Certification Test Engine to PDF

Get The Important Preparation Guide With ARA-C01 Dumps

To become SnowPro Advanced Architect certified, candidates must pass the Snowflake ARA-C01 exam. ARA-C01 exam is designed to test the candidate’s ability to design and implement advanced Snowflake solutions, as well as their ability to troubleshoot and optimize Snowflake implementations. The SnowPro Advanced Architect certification is a valuable credential for architects and engineers who work with the Snowflake platform, as it demonstrates their expertise in designing and implementing complex Snowflake solutions. SnowPro Advanced Architect Certification certification is recognized by Snowflake and its partners and is a valuable asset for those looking to advance their career in the data warehousing and data analytics space.

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.

Q41. A healthcare company wants to share data with a medical institute. The institute is running a Standard edition of Snowflake; the healthcare company is running a Business Critical edition.
How can this data be shared?

The healthcare company will need to change the institute’s Snowflake edition in the accounts panel.

By default, sharing is supported from a Business Critical Snowflake edition to a Standard edition.

Contact Snowflake and they will execute the share request for the healthcare company.

Set the share_restriction parameter on the shared object to false.

Q42. The data share exists between a data provider account and a data consumer account. Five tables from the provider account are being shared with the consumer account. The consumer role has been granted the imported privileges privilege.
What will happen to the consumer account if a new table (table_6) is added to the provider schema?

The consumer role will automatically see the new table and no additional grants are needed.

The consumer role will see the table only after this grant is given on the consumer side:
grant imported privileges on database PSHARE_EDW_4TEST_DB to DEV_ROLE;

The consumer role will see the table only after this grant is given on the provider side:
use role accountadmin;
Grant select on table EDW.ACCOUNTING.Table_6 to share PSHARE_EDW_4TEST;

The consumer role will see the table only after this grant is given on the provider side:
use role accountadmin;
grant usage on database EDW to share PSHARE_EDW_4TEST ;
grant usage on schema EDW.ACCOUNTING to share PSHARE_EDW_4TEST ;
Grant select on table EDW.ACCOUNTING.Table_6 to database PSHARE_EDW_4TEST_DB ;

Q43. 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.

Explanation
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 incorrectbecause 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. References: Introduction to Secure Data Sharing | Snowflake Documentation, Cloning Objects | Snowflake Documentation, Time Travel | Snowflake Documentation, Working with Shares | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation

Q44. 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.

Q45. A DevOps team has a requirement for recovery of staging tables used in a complex set of data pipelines. The staging tables are all located in the same staging schema. One of the requirements is to have online recovery of data on a rolling 7-day basis.
After setting up the DATA_RETENTION_TIME_IN_DAYS at the database level, certain tables remain unrecoverable past 1 day.
What would cause this to occur? (Choose two.)

The staging schema has not been setup for MANAGED ACCESS.

The DATA_RETENTION_TIME_IN_DAYS for the staging schema has been set to 1 day.

The tables exceed the 1 TB limit for data recovery.

The staging tables are of the TRANSIENT type.

The DevOps role should be granted ALLOW_RECOVERY privilege on the staging schema.

* The DATA_RETENTION_TIME_IN_DAYS parameter controls the Time Travel retention period for an object (database, schema, or table) in Snowflake. This parameter specifies the number of days for
* which historical data is preserved and can be accessed using Time Travel operations (SELECT, CREATE … CLONE, UNDROP)1.
* The requirement for recovery of staging tables on a rolling 7-day basis means that the DATA_RETENTION_TIME_IN_DAYS parameter should be set to 7 at the database level. However, this parameter can be overridden at the lower levels (schema or table) if they have a different value1.
* Therefore, one possible cause for certain tables to remain unrecoverable past 1 day is that the DATA_RETENTION_TIME_IN_DAYS for the staging schema has been set to 1 day. This would override the database level setting and limit the Time Travel retention period for all the tables in the schema to 1 day. To fix this, the parameter should be unset or set to 7 at the schema level1. Therefore, option B is correct.
* Another possible cause for certain tables to remain unrecoverable past 1 day is that the staging tables are of the TRANSIENT type. Transient tables are tables that do not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. Transient tables are suitable for temporary or intermediate data that can be easily reproduced or replicated2. To fix this, the tables should be created as permanent tables, which can have a Time Travel retention period of up to 90 days1. Therefore, option D is correct.
* Option A is incorrect because the MANAGED ACCESS feature is not related to the data recovery requirement. MANAGED ACCESS is a feature that allows granting access privileges to objects without explicitly granting the privileges to roles. It does not affect the Time Travel retention period or the data availability3.
* Option C is incorrect because there is no 1 TB limit for data recovery in Snowflake. The data storage size does not affect the Time Travel retention period or the data availability4.
* Option E is incorrect because there is no ALLOW_RECOVERY privilege in Snowflake. The privilege required to perform Time Travel operations is SELECT, which allows querying historical data in tables5.
References: : Understanding & Using Time Travel : Transient Tables : Managed Access : Understanding Storage Cost : Table Privileges

Q46. Which command will you run to list all privileges and roles granted to the role

SHOW GRANTS TO ROLE <ROLE NAME>

SHOW GRANTS ON ROLE <ROLE NAME>

SHOW GRANTS OF ROLE <ROLE NAME>

SHOW GRANTS FOR ROLE <ROLE NAME>

Q47. The endpoint insertFiles of SnowPipe rest API is used to inform Snowflake about the files to be ingested into a table. Select the two statements for this end point.

The post can contain at most 5000 files.

Each file path given must be <= 1024 bytes long when serialized as UTF-8

The post can contain unlimited number of files.

Q48. A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?

Create accounts for each tenant in the Snowflake organization.

Create an object for each tenant strategy if row level security is viable for isolating tenants.

Create an object for each tenant strategy if row level security is not viable for isolating tenants.

Create a multi-tenant table strategy if row level security is not viable for isolating tenants.

Q49. A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?

Create accounts for each tenant in the Snowflake organization.

Create an object for each tenant strategy if row level security is viable for isolating tenants.

Create an object for each tenant strategy if row level security is not viable for isolating tenants.

Create a multi-tenant table strategy if row level security is not viable for isolating tenants.

Q50. 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.
Reference:
Context Functions
Advanced Column-level Security topics
Snowflake Data Governance: Column Level Security Overview
Data Security Snowflake Part 2 – Column Level Security

Q51. Multi-cluster warehouses are best utilized for

Scaling resources to improve concurrency for users/queries

Improving the performance of slow-running queries

Improving the performance of data loading

Q52. You have created a table as below
CREATE TABLE SNOWFLAKE (FLAKE_ID INTEGER, UDEMY_COURSE VARCHAR);
Which of the below select query will fail for this table?

SELECT * from snowflake;

SELECT * from Snowflake;

SELECT * from “snowflake”;

SELECT * FROM “SNOWFLAKE”;

Q53. The diagram shows the process flow for Snowpipe auto-ingest with Amazon Simple Notification Service (SNS) with the following steps:
Step 1: Data files are loaded in a stage.
Step 2: An Amazon S3 event notification, published by SNS, informs Snowpipe – by way of Amazon Simple Queue Service (SQS) – that files are ready to load. Snowpipe copies the files into a queue.
Step 3: A Snowflake-provided virtual warehouse loads data from the queued files into the target table based on parameters defined in the specified pipe.

If an AWS Administrator accidentally deletes the SQS subscription to the SNS topic in Step 2, what will happen to the pipe that references the topic to receive event messages from Amazon S3?

The pipe will continue to receive the messages as Snowflake will automatically restore the subscription to the same SNS topic and will recreate the pipe by specifying the same SNS topic name in the pipe definition.

The pipe will no longer be able to receive the messages and the user must wait for 24 hours from the time when the SNS topic subscription was deleted. Pipe recreation is not required as the pipe will reuse the same subscription to the existing SNS topic after 24 hours.

The pipe will continue to receive the messages as Snowflake will automatically restore the subscription by creating a new SNS topic. Snowflake will then recreate the pipe by specifying the new SNS topic name in the pipe definition.

The pipe will no longer be able to receive the messages. To restore the system immediately, the user needs to manually create a new SNS topic with a different name and then recreate the pipe by specifying the new SNS topic name in the pipe definition.

Q54. Below are the rest APIs provided by Snowpipe

insertFiles

insertReport

loadData

Q55. Refer to the exhibit.

Based on the architecture in the image, how can the data from DB1 be copied into TBL2? (Select TWO).

Q56. A Snowflake Architect Is working with Data Modelers and Table Designers to draft an ELT framework specifically for data loading using Snowpipe. The Table Designers will add a timestamp column that Inserts the current tlmestamp as the default value as records are loaded into a table. The Intent is to capture the time when each record gets loaded into the table; however, when tested the timestamps are earlier than the loae_take column values returned by the copy_history function or the Copy_HISTORY view (Account Usage).
Why Is this occurring?

The timestamps are different because there are parameter setup mismatches. The parameters need to be realigned

The Snowflake timezone parameter Is different from the cloud provider’s parameters causing the mismatch.

The Table Designer team has not used the localtimestamp or systimestamp functions in the Snowflake copy statement.

The CURRENT_TIMEis evaluated when the load operation is compiled in cloud services rather than when the record is inserted into the table.

The correct answer is D because the CURRENT_TIME function returns the current timestamp at the start of the statement execution, not at the time of the record insertion. Therefore, if the load operation takes some time to complete, the CURRENT_TIME value may be earlier than the actual load time.
Option A is incorrect because the parameter setup mismatches do not affect the timestamp values. The parameters are used to control the behavior and performance of the load operation, such as the file format, the error handling, the purge option, etc.
Option B is incorrect because the Snowflake timezone parameter and the cloud provider’s parameters are independent of each other. The Snowflake timezone parameter determines the session timezone for displaying and converting timestamp values, while the cloud provider’s parameters determine the physical location and configuration of the storage and compute resources.
Option C is incorrect because the localtimestamp and systimestamp functions are not relevant for the Snowpipe load operation. The localtimestamp function returns the current timestamp in the session timezone, while the systimestamp function returns the current timestamp in the system timezone. Neither of them reflect the actual load time of the records. Reference:
Snowflake Documentation: Loading Data Using Snowpipe: This document explains how to use Snowpipe to continuously load data from external sources into Snowflake tables. It also describes the syntax and usage of the COPY INTO command, which supports various options and parameters to control the loading behavior.
Snowflake Documentation: Date and Time Data Types and Functions: This document explains the different data types and functions for working with date and time values in Snowflake. It also describes how to set and change the session timezone and the system timezone.
Snowflake Documentation: Querying Metadata: This document explains how to query the metadata of the objects and operations in Snowflake using various functions, views, and tables. It also describes how to access the copy history information using the COPY_HISTORY function or the COPY_HISTORY view.

Q57. An Architect needs to design a solution for building environments for development, test, and pre-production, all located in a single Snowflake account. The environments should be based on production data.
Which solution would be MOST cost-effective and performant?

Use zero-copy cloning into transient tables.

Use zero-copy cloning into permanent tables.

Use CREATE TABLE … AS SELECT (CTAS) statements.

Use a Snowflake task to trigger a stored procedure to copy data.

Q58. A user has the appropriate privilege to see unmasked data in a column.
If the user loads this column data into another column that does not have a masking policy, what will occur?

Unmasked data will be loaded in the new column.

Masked data will be loaded into the new column.

Unmasked data will be loaded into the new column but only users with the appropriate privileges will be able to see the unmasked data.

Unmasked data will be loaded into the new column and no users will be able to see the unmasked data.

Q59. 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?

Ask the vendor to create a Snowflake account, load the data into Snowflake and create a data share.

Create an external stage on Google Cloud Storage and use the external table to load the data into Snowflake.

Copy the data from Google Cloud Storage to Azure Blob storage using external tools and load data from Blob storage to Snowflake.

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.

Q60. A media company needs a data pipeline that will ingest customer review data into a Snowflake table, and apply some transformations. The company also needs to use Amazon Comprehend to do sentiment analysis and make the de-identified final data set available publicly for advertising companies who use different cloud providers in different regions.
The data pipeline needs to run continuously ang efficiently as new records arrive in the object storage leveraging event notifications. Also, the operational complexity, maintenance of the infrastructure, including platform upgrades and security, and the development effort should be minimal.
Which design will meet these requirements?

Ingest the data using COPY INTO and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.

Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Create an external function to do model inference with Amazon Comprehend and write the final records to a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.

Ingest the data into Snowflake using Amazon EMR and PySpark using the Snowflake Spark connector.
Apply transformations using another Spark job. Develop a python program to do model inference by leveraging the Amazon Comprehend text analysis API. Then write the results to a Snowflake table and create a listing in the Snowflake Marketplace to make the data available to other companies.

Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.

Q61. A company is designing high availability and disaster recovery plans and needs to maximize redundancy and minimize recovery time objectives for their critical application processes. Cost is not a concern as long as the solution is the best available. The plan so far consists of the following steps:
1. Deployment of Snowflake accounts on two different cloud providers.
2. Selection of cloud provider regions that are geographically far apart.
3. The Snowflake deployment will replicate the databases and account data between both cloud provider accounts.
4. Implementation of Snowflake client redirect.
What is the MOST cost-effective way to provide the HIGHEST uptime and LEAST application disruption if there is a service event?

Connect the applications using the <organization_name>-<connection_name> URL. Use the Business Critical Snowflake edition.

Connect the applications using the <organization_name>-<connection_name> URL. Use the Virtual Private Snowflake (VPS) edition.

Connect the applications using the <organization_name>-<accountLocator> URL. Use the Enterprise Snowflake edition.

Connect the applications using the <organization_name>-<accountLocator> URL. Use the Business Critical Snowflake edition.

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163 Q&As in UPDATED ARA-C01 Exam Questions Certification Test Engine to PDF [Q41-Q61]

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