codifyedu.com

Frank Miller Frank Miller

0 Course Enrolled • 0 Course Completed

Biography

ARA-C01 Test Cram Review, ARA-C01 Latest Exam Testking

DOWNLOAD the newest PassCollection ARA-C01 PDF dumps from Cloud Storage for free: https://drive.google.com/open?id=10GCozWjPJj35ykMfz_1s8ddiEcCBHvMp

The second format is a web-based practice exam which offers a flexible and accessible option for students trying to assess and improve their preparation for the Snowflake Certification Exams. The ARA-C01 web-based practice test can be accessed online through browsers like Firefox, Microsoft Edge, Google Chrome, and Safari. Customers need a stable internet connection in order to access web-based formats easily without facing issues.

Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Certification Exam is a certification program designed for IT professionals who want to demonstrate their expertise in architecting data solutions using Snowflake. ARA-C01 Exam is intended for individuals who have already obtained the SnowPro Core or SnowPro Advanced certification and have experience working with Snowflake as a data warehousing platform.

>> ARA-C01 Test Cram Review <<

Pass Your Snowflake ARA-C01 Exam With An Excellent Score

If you are still hesitating about whether you can get ARA-C01 certification through the exam, we believed that our ARA-C01 study materials will be your best choice, it will tell you that passing the exam is no longer a dream for you, and it will be your best assistant on the way to passing the exam. Tens of thousands of our customers have benefited from our ARA-C01 Exam Braindumps and got their certifications. So you will as long as you choose to buy our ARA-C01 practice guide.

Snowflake ARA-C01 Certification Exam is an advanced-level exam that requires a deep understanding of Snowflake's architecture and best practices. ARA-C01 exam is designed to test an individual's ability to design and build scalable, secure, and high-performing data solutions on the Snowflake platform. ARA-C01 exam is intended for professionals who have several years of experience in data architecture and engineering and are seeking to validate their skills and demonstrate their expertise in the Snowflake ecosystem. Passing the SnowPro Advanced Architect Certification Exam can help professionals gain recognition in the industry and demonstrate their competence to potential employers.

Snowflake ARA-C01 Certification Exam is a highly valued credential in the data industry. It is designed to test a candidate's advanced architectural knowledge of Snowflake's cloud data platform. Passing the exam is a significant achievement for any data professional looking to advance their career in the field. SnowPro Advanced Architect Certification certification demonstrates that you have a deep understanding of Snowflake's architecture, data modeling, performance tuning, security, and data integration, making you a valuable asset to any organization.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q67-Q72):

NEW QUESTION # 67
Consider the following scenario where a masking policy is applied on the CREDICARDND column of the CREDITCARDINFO table. The masking policy definition Is as follows:

Sample data for the CREDITCARDINFO table is as follows:
NAME EXPIRYDATE CREDITCARDNO
JOHN DOE 2022-07-23 4321 5678 9012 1234
if the Snowflake system rotes have not been granted any additional roles, what will be the result?

A. The owner of the table will see the CREDICARDND column data in clear text.
B. Anyone with the Pl_ANALYTICS role will see the last 4 characters of the CREDICARDND column data in dear text.
C. Anyone with the Pl_ANALYTICS role will see the CREDICARDND column as*** 'MASKED* **'.
D. The sysadmin can see the CREDICARDND column data in clear text.

Answer: C

Explanation:
* The masking policy defined in the image indicates that if a user has the PI_ANALYTICS role, they will be able to see the last 4 characters of the CREDITCARDNO column data in clear text. Otherwise, they will see 'MASKED'. Since Snowflake system roles have not been granted any additional roles, they won't have the PI_ANALYTICS role and therefore cannot view the last 4 characters of credit card numbers.
* To apply a masking policy on a column in Snowflake, you need to use the ALTER TABLE ... ALTER COLUMN command or the ALTER VIEW command and specify the policy name. For example, to apply the creditcardno_mask policy on the CREDITCARDNO column of the CREDITCARDINFO table, you can use the following command:
ALTER TABLE CREDITCARDINFO ALTER COLUMN CREDITCARDNO SET MASKING POLICY creditcardno_mask;
* For more information on how to create and use masking policies in Snowflake, you can refer to the following resources:
CREATE MASKING POLICY: This document explains the syntax and usage of the CREATE MASKING POLICY command, which allows you to create a new masking policy or replace an existing one.
Using Dynamic Data Masking: This guide provides instructions on how to configure and use dynamic data masking in Snowflake, which is a feature that allows you to mask sensitive data based on the execution context of the user.
ALTER MASKING POLICY: This document explains the syntax and usage of the ALTER MASKING POLICY command, which allows you to modify the properties of an existing masking policy.
References: 1: https://docs.snowflake.com/en/sql-reference/sql/create-masking-policy 2:
https://docs.snowflake.com/en/user-guide/security-column-ddm-use 3:
https://docs.snowflake.com/en/sql-reference/sql/alter-masking-policy

NEW QUESTION # 68
What are some of the characteristics of result set caches? (Choose three.)

A. Snowflake persists the data results for 24 hours.
B. Time Travel queries can be executed against the result set cache.
C. The retention period can be reset for a maximum of 31 days.
D. The result set cache is not shared between warehouses.
E. The data stored in the result cache will contribute to storage costs.
F. Each time persisted results for a query are used, a 24-hour retention period is reset.

Answer: A,D,F

Explanation:
In Snowflake, the characteristics of result set caches include persistence of data results for 24 hours (B), each use of persisted results resets the 24-hour retention period (C), and result set caches are not shared between different warehouses (F). The result set cache is specifically designed to avoid repeated execution of the same query within this timeframe, reducing computational overhead and speeding up query responses. These caches do not contribute to storage costs, and their retention period cannot be extended beyond the default duration nor up to 31 days, as might be misconstrued.
Reference: Snowflake Documentation on Result Set Caching.

NEW QUESTION # 69
Cloud services can help in pruning even if the columns are variant columns.

A. FALSE
B. TRUE

Answer: B

NEW QUESTION # 70
You have created a table as below
CREATE TABLE SNOWFLAKE_BLOG(BLOG_ID NUMBER, BLOG_CONTENT VARCHAR,BLOG_AUTHOR VARCHAR,BLOG_CREATE_DATE TIMESTAMP );
Now you want to cluster it by BLOG_AUTHOR and BLOG_CREATE_DATE.
Which command below will you choose?

A. ALTER TABLE SNOWFLAKE_BLOG CLUSTER BY (BLOG_AUTHOR, BLOG_CREATE_DATE);
B. ALTER TABLE SNOWFLAKE_BLOG CLUSTER BY (BLOG_AUTHOR)
C. ALTER TABLE SNOWFLAKE_BLOG CLUSTER BY (BLOG_CREATE_DATE);

Answer: A

NEW QUESTION # 71
Why might a Snowflake Architect use a star schema model rather than a 3NF model when designing a data architecture to run in Snowflake? (Select TWO).

A. The Bl tool needs a data model that allows users to summarize facts across different dimensions, or to drill down from the summaries.
B. Snowflake cannot handle the joins implied in a 3NF data model.
C. The Architect wants to present a simple flattened single view of the data to a particular group of end users.
D. The Architect wants to remove data duplication from the data stored in Snowflake.
E. The Architect is designing a landing zone to receive raw data into Snowflake.

Answer: A,C

Explanation:
A star schema model is a type of dimensional data model that consists of a single fact table and multiple dimension tables. A 3NF model is a type of relational data model that follows the third normal form, which eliminates data redundancy and ensures referential integrity. A Snowflake Architect might use a star schema model rather than a 3NF model when designing a data architecture to run in Snowflake for the following reasons:
* A star schema model is more suitable for analytical queries that require aggregating and slicing data across different dimensions, such as those performed by a BI tool. A 3NF model is more suitable for transactional queries that require inserting, updating, and deleting individual records.
* A star schema model is simpler and faster to query than a 3NF model, as it involves fewer joins and less complex SQL statements. A 3NF model is more complex and slower to query, as it involves more joins and more complex SQL statements.
* A star schema model can provide a simple flattened single view of the data to a particular group of end users, such as business analysts or data scientists, who need to explore and visualize the data. A 3NF model can provide a more detailed and normalized view of the data to a different group of end users, such as application developers or data engineers, who need to maintain and update the data.
The other options are not valid reasons for choosing a star schema model over a 3NF model in Snowflake:
* Snowflake can handle the joins implied in a 3NF data model, as it supports ANSI SQL and has a powerful query engine that can optimize and execute complex queries efficiently.
* The Architect can use both star schema and 3NF models to remove data duplication from the data stored in Snowflake, as both models can enforce data integrity and avoid data anomalies. However, the trade-off is that a star schema model may have more data redundancy than a 3NF model, as it denormalizes the data for faster query performance, while a 3NF model may have less data redundancy than a star schema model, as it normalizes the data for easier data maintenance.
* The Architect can use both star schema and 3NF models to design a landing zone to receive raw data into Snowflake, as both models can accommodate different types of data sources and formats. However, the choice of the model may depend on the purpose and scope of the landing zone, such as whether it is a temporary or permanent storage, whether it is a staging area or a data lake, and whether it is a single source or a multi-source integration.
References:
* Snowflake Architect Training
* Data Modeling: Understanding the Star and Snowflake Schemas
* Data Vault vs Star Schema vs Third Normal Form: Which Data Model to Use?
* Star Schema vs Snowflake Schema: 5 Key Differences
* Dimensional Data Modeling - Snowflake schema
* Star schema vs Snowflake Schema

NEW QUESTION # 72
......

ARA-C01 Latest Exam Testking: https://www.passcollection.com/ARA-C01_real-exams.html

BONUS!!! Download part of PassCollection ARA-C01 dumps for free: https://drive.google.com/open?id=10GCozWjPJj35ykMfz_1s8ddiEcCBHvMp

Frank Miller Frank Miller

Biography

Main Menu

Courses