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Snowflake ARA-C01 Exam covers a wide range of topics, including Snowflake architecture, data modeling, security, performance optimization, and data integration. ARA-C01 exam consists of multiple-choice questions that test the aspirant's knowledge of Snowflake's core concepts, features, and capabilities. ARA-C01 exam is designed to assess the aspirant's ability to design and implement Snowflake solutions that are scalable, secure, and meet the business requirements. By passing the Snowflake ARA-C01 Exam, aspirants can demonstrate their expertise in Snowflake architecture and gain recognition as a SnowPro Advanced Architect.

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Snowflake ARA-C01: SnowPro Advanced Architect Certification Exam is an essential step for professionals looking to advance their careers in the field of data warehousing and cloud computing. It is designed to test an individual's knowledge and expertise in advanced Snowflake architecture and is a valuable accomplishment that demonstrates an individual's commitment to the platform.

Snowflake ARA-C01 Certification is an advanced-level certification exam that is designed to validate the skills and knowledge of the candidates in the field of Snowflake data warehousing. SnowPro Advanced Architect Certification certification exam is intended for experienced professionals who have a deep understanding of Snowflake architecture, its various components, and their respective functionalities. SnowPro Advanced Architect Certification certification exam is an ideal choice for architects, consultants, and data engineers who work with Snowflake on a daily basis.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q51-Q56):

NEW QUESTION # 51
Refreshing a secondary database is not allowed in the following circumstances

A. Materialized views
B. Primary database has external table
C. Databases created from shares
D. Primary database contains transient tables

Answer: B,C

NEW QUESTION # 52
Which command will create a schema without Fail-safe and will restrict object owners from passing on access to other users?

A. create schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS - 7;
B. create TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 7;
C. create schema EDW.ACCOUNTING WITH MANAGED ACCESS;
D. create TRANSIENT schema EDW.ACCOUNTING WITH MANAGED ACCESS DATA_RETENTION_TIME_IN_DAYS = 1;

Answer: B

Explanation:
A transient schema in Snowflake is designed without a Fail-safe period, meaning it does not incur additional storage costs once it leaves Time Travel, and it is not protected by Fail-safe in the event of a data loss. The WITH MANAGED ACCESS option ensures that all privilege grants, including future grants on objects within the schema, are managed by the schema owner, thus restricting object owners from passing on access to other users1.
Reference =
* Snowflake Documentation on creating schemas1
* Snowflake Documentation on configuring access control2
* Snowflake Documentation on understanding and viewing Fail-safe3

NEW QUESTION # 53
A company is designing a process for importing a large amount of loT JSON data from cloud storage into Snowflake. New sets of loT data get generated and uploaded approximately every 5 minutes.
Once the loT data is in Snowflake, the company needs up-to-date information from an external vendor to join to the data. This data is then presented to users through a dashboard that shows different levels of aggregation.
The external vendor is a Snowflake customer.
What solution will MINIMIZE complexity and MAXIMIZE performance?

A. 1. Create an external table over the JSON data in cloud storage.
2. Create a task that runs every 5 minutes to run a transformation procedure on new data, based on a saved timestamp.
3. Ask the vendor to expose an API so an external function can be used to generate a call to join the data back to the loT data in the transformation procedure.
4. Give the transformed table access to the dashboard tool.
5. Perform the aggregations on the dashboard tool.
B. 1. Create an external table over the JSON data in cloud storage.
2. Create a task that runs every 5 minutes to run a transformation procedure on new data based on a saved timestamp.
3. Ask the vendor to create a data share with the required data that can be imported into the company's Snowflake account.
4. Join the vendor's data back to the loT data using a transformation procedure.
5. Create views over the larger dataset to perform the aggregations required by the dashboard.
6. Give the views access to the dashboard tool.
C. 1. Create a Snowpipe to bring the JSON data into Snowflake.
2. Use streams and tasks to trigger a transformation procedure when new JSON data arrives.
3. Ask the vendor to create a data share with the required data that is then imported into the Snowflake account.
4. Join the vendor's data back to the loT data in a transformation procedure
5. Create materialized views over the larger dataset to perform the aggregations required by the dashboard.
6. Give the materialized views access to the dashboard tool.
D. 1. Create a Snowpipe to bring the JSON data into Snowflake.
2. Use streams and tasks to trigger a transformation procedure when new JSON data arrives.
3. Ask the vendor to expose an API so an external function call can be made to join the vendor's data back to the loT data in a transformation procedure.
4. Create materialized views over the larger dataset to perform the aggregations required by the dashboard.
5. Give the materialized views access to the dashboard tool.

Answer: C

Explanation:
Using Snowpipe for continuous, automated data ingestion minimizes the need for manual intervention and ensures that data is available in Snowflake promptly after it is generated. Leveraging Snowflake's data sharing capabilities allows for efficient and secure access to the vendor's data without the need for complex API integrations. Materialized views provide pre-aggregated data for fast access, which is ideal for dashboards that require high performance1234.
References =
*Snowflake Documentation on Snowpipe4
*Snowflake Documentation on Secure Data Sharing2
*Best Practices for Data Ingestion with Snowflake1

NEW QUESTION # 54
An Architect configures the following timeouts and creates a task using a size X-Small warehouse. The task's INSERT statement will take ~40 hours.
How long will the INSERT execute?

A. 40 hours
B. 1 minute
C. 1 hour
D. 5 minutes

Answer: B

Explanation:
Tasks in Snowflake are governed by the USER_TASK_TIMEOUT_MS parameter, which specifies the maximum execution time for a single task run. In this scenario, USER_TASK_TIMEOUT_MS = 60000, which equals 1 minute. This timeout applies regardless of account-, session-, or warehouse-level statement timeout settings.
Even though the account, session, and warehouse statement timeouts are higher, the task-specific timeout takes precedence for task execution. As a result, the INSERT statement will be terminated after 1 minute (Answer A).
This is a key SnowPro Architect concept: tasks have their own execution limits that override other timeout parameters. Architects must ensure that task timeouts are configured appropriately for long-running operations or redesign workloads to fit within task constraints.
=========

NEW QUESTION # 55
An Architect Is designing a data lake with Snowflake. The company has structured, semi-structured, and unstructured dat a. The company wants to save the data inside the data lake within the Snowflake system. The company is planning on sharing data among Its corporate branches using Snowflake data sharing.
What should be considered when sharing the unstructured data within Snowflake?

A. A pre-signed URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with no time limit for the URL.
B. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with the "expiration_time" argument defined for the URL time limit.
C. A scoped URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 24-hour time limit for the URL.
D. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 7-day time limit for the URL.

Answer: B

Explanation:
According to the Snowflake documentation, unstructured data files can be shared by using a secure view and Secure Data Sharing. A secure view allows the result of a query to be accessed like a table, and a secure view is specifically designated for data privacy. A scoped URL is an encoded URL that permits temporary access to a staged file without granting privileges to the stage. The URL expires when the persisted query result period ends, which is currently 24 hours. A scoped URL is recommended for file administrators to give scoped access to data files to specific roles in the same account. Snowflake records information in the query history about who uses a scoped URL to access a file, and when. Therefore, a scoped URL is the best option to share unstructured data within Snowflake, as it provides security, accountability, and control over the data access. Reference:
Sharing unstructured Data with a secure view
Introduction to Loading Unstructured Data

NEW QUESTION # 56
......

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