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Snowflake ARA-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Accounts and Security	25%	- Account and database strategy design - Security, compliance and governance architecture - Security principles and implementation scenarios
Topic 2: Snowflake Architecture	30%	- Development lifecycle and workload support - Data modeling and use cases - Data sharing architecture design - Data protection and recovery strategies - Object hierarchy and architectural impact
Topic 3: Data Engineering	25%	- Transformation and processing frameworks - Data loading and unloading solutions - Data pipeline and integration design
Topic 4: Performance Optimization	20%	- Cost optimization and resource management - Virtual warehouse configuration and sizing - Clustering and partitioning strategies - Query performance tuning

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q146-Q151):

NEW QUESTION # 146
A user can change object parameters using which of the following roles?

A. ACCOUNTADMIN, SECURITYADMIN
B. SECURITYADMIN, USER with PRIVILEGE
C. ACCOUNTADMIN, USER with PRIVILEGE
D. SYSADMIN, SECURITYADMIN

Answer: C

Explanation:
According to the Snowflake documentation, object parameters are parameters that can be set on individual objects such as databases, schemas, tables, and stages. Object parameters can be set by users with the appropriate privileges on the objects. For example, to set the object parameter AUTO_REFRESH on a table, the user must have the MODIFY privilege on the table. The ACCOUNTADMIN role has the highest level of privileges on all objects in the account, so it can set any object parameter on any object. However, other roles, such as SECURITYADMIN or SYSADMIN, do not have the same level of privileges on all objects, so they cannot set object parameters on objects they do not own or have the required privileges on. Therefore, the correct answer is C. ACCOUNTADMIN, USER with PRIVILEGE.
Parameters | Snowflake Documentation
Object Parameters | Snowflake Documentation
Object Privileges | Snowflake Documentation

NEW QUESTION # 147
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?

A. Use zero-copy cloning into permanent tables.
B. Use a Snowflake task to trigger a stored procedure to copy data.
C. Use zero-copy cloning into transient tables.
D. Use CREATE TABLE ... AS SELECT (CTAS) statements.

Answer: C

Explanation:
Zero-copy cloning is a feature in Snowflake that allows for the creation of a clone of a database, schema, or table without duplicating any data, which is cost-effective as it saves on storage costs. Transient tables are temporary and do not incur storage costs for the time they are not accessed, making them a cost-effective option for development, test, and pre-production environments that do not require the durability of permanent tables123.
Reference
* Snowflake Documentation on Zero-Copy Cloning3.
* Articles discussing the cost-effectiveness and performance benefits of zero-copy cloning12.

NEW QUESTION # 148
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).

A. Role-Based Access Control (RBAC)
B. Dynamic Data Masking
C. Materialized views
D. External tokenization
E. Object tagging

Answer: A,B

Explanation:
Dynamic Data Masking is a Snowflake security feature that conditionally masks or reveals column values at query time based on the executing role (Answer D). This allows privileged users (such as object owners or compliance roles) to see clear-text PII/PHI, while other users see masked or tokenized values. Because masking is evaluated at query time, it supports de-tokenization logic when the role is authorized.
Role-Based Access Control (RBAC) underpins this behavior by defining which roles are privileged and allowed to view unmasked data (Answer E). Masking policies are evaluated in the context of the active role, making RBAC essential for enforcing correct access.
Object tagging alone does not enforce access control. Materialized views duplicate data and do not support dynamic de-tokenization logic. External tokenization is not required when Snowflake masking policies can handle conditional reveal. This question tests SnowPro Architect knowledge of advanced column-level security and privacy controls.
=========

NEW QUESTION # 149
Consider the following COPY command which is loading data with CSV format into a Snowflake table from an internal stage through a data transformation query.

This command results in the following error:
SQL compilation error: invalid parameter 'validation_mode'
Assuming the syntax is correct, what is the cause of this error?

A. The value return_all_errors of the option VALIDATION_MODE is causing a compilation error.
B. The VALIDATION_MODE parameter does not support COPY statements with CSV file formats.
C. The VALIDATION_MODE parameter does not support COPY statements that transform data during a load.
D. The VALIDATION_MODE parameter supports COPY statements that load data from external stages only.

Answer: C

Explanation:
* The VALIDATION_MODE parameter is used to specify the behavior of the COPY statement when loading data into a table. It is used to specify whether the COPY statement should return an error if any of the rows in the file are invalid or if it should continue loading the valid rows. The VALIDATION_MODE parameter is only supported for COPY statements that load data from external stages1.
* The query in the question uses a data transformation query to load data from an internal stage. A data transformation query is a query that transforms the data during the load process, such as parsing JSON or XML data, applying functions, or joining with other tables2.
* According to the documentation, VALIDATION_MODE does not support COPY statements that transform data during a load. If the parameter is specified, the COPY statement returns an error1.
Therefore, option C is the correct answer.
References: : COPY INTO <table> : Transforming Data During a Load\

NEW QUESTION # 150
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 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.
C. 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.
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 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.

Answer: D

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.
Reference =
* Snowflake Documentation on Snowpipe4
* Snowflake Documentation on Secure Data Sharing2
* Best Practices for Data Ingestion with Snowflake1

NEW QUESTION # 151
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New developments in the tech sector always bring new job opportunities. These new jobs have to be filled with the SnowPro Advanced Architect Certification (ARA-C01) certification holders. So to fill the space, you need to pass the Snowflake ARA-C01 exam. Earning the SnowPro Advanced Architect Certification (ARA-C01) certification helps you clear the obstacles you face while working in the Snowflake field. To get prepared for the SnowPro Advanced Architect Certification (ARA-C01) certification exam, applicants face a lot of trouble if the study material is not updated.

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