Spring Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

ARA-R01 Exam Dumps : SnowPro Advanced: Architect Recertification Exam

PDF
ARA-R01 pdf
 Real Exam Questions and Answer
 Last Update: Feb 16, 2026
 Question and Answers: 162 With Explanation
 Compatible with all Devices
 Printable Format
 100% Pass Guaranteed
$25.5  $84.99
ARA-R01 exam
PDF + Testing Engine
ARA-R01 PDF + engine
 Both PDF & Practice Software
 Last Update: Feb 16, 2026
 Question and Answers: 162
 Discount Offer
 Download Free Demo
 24/7 Customer Support
$40.5  $134.99
Testing Engine
ARA-R01 Engine
 Desktop Based Application
 Last Update: Feb 16, 2026
 Question and Answers: 162
 Create Multiple Test Sets
 Questions Regularly Updated
  90 Days Free Updates
  Windows and Mac Compatible
$30  $99.99

Verified By IT Certified Experts

CertsTopics.com Certified Safe Files

Up-To-Date Exam Study Material

99.5% High Success Pass Rate

100% Accurate Answers

Instant Downloads

Exam Questions And Answers PDF

Try Demo Before You Buy

Certification Exams with Helpful Questions And Answers

SnowPro Advanced: Architect Recertification Exam Questions and Answers

Question 1

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?

Options:

A.

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

B.

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

C.

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

D.

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

Buy Now
Question 2

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

Options:

A.

Graph model

B.

Dimensional/Kimball

C.

Data lake

D.

lnmon/3NF

E.

Bayesian hierarchical model

F.

Data vault

Question 3

A company has a source system that provides JSON records for various loT operations. The JSON Is loading directly into a persistent table with a variant field. The data Is quickly growing to 100s of millions of records and performance to becoming an issue. There is a generic access pattern that Is used to filter on the create_date key within the variant field.

What can be done to improve performance?

Options:

A.

Alter the target table to Include additional fields pulled from the JSON records. This would Include a create_date field with a datatype of time stamp. When this field Is used in the filter, partition pruning will occur.

B.

Alter the target table to include additional fields pulled from the JSON records. This would include a create_date field with a datatype of varchar. When this field is used in the filter, partition pruning will occur.

C.

Validate the size of the warehouse being used. If the record count is approaching 100s of millions, size XL will be the minimum size required to process this amount of data.

D.

Incorporate the use of multiple tables partitioned by date ranges. When a user or process needs to query a particular date range, ensure the appropriate base table Is used.