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  1. Home
  2. Snowflake Certification
  3. ARA-R01 Exam
  4. Snowflake.ARA-R01.v2024-10-29.q82 Dumps
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Question 6

A Snowflake Architect created a new data share and would like to verify that only specific records in secure views are visible within the data share by the consumers.
What is the recommended way to validate data accessibility by the consumers?

Correct Answer: C
The SIMULATED_DATA_SHARING_CONSUMER session parameter allows a data provider to simulate the data access of a consumer account without creating a reader account or logging in with the consumer credentials. This parameter can be used to validate the data accessibility by the consumers in a data share, especially when using secure viewsor secure UDFs that filter data based on the current account or role. By setting this parameter to the name of a consumer account, the data provider can see the same data as the consumer would see when querying the shared database. This is a convenient and efficient way to test the data sharing functionality and ensure that only the intended data is visible to the consumers.
References:
Using the SIMULATED_DATA_SHARING_CONSUMER Session Parameter
SnowPro Advanced: Architect Exam Study Guide
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Question 7

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?

Correct Answer: C
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
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Question 8

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?

Correct Answer: D
By default, Snowflake does not allow sharing data from a Business Critical edition to a non-Business Critical edition. This is because Business Critical edition provides enhanced security and data protection features that are not available in lower editions. However, this restriction can be overridden by setting the share_restriction parameter on the shared object (database, schema, or table) to false. This parameter allows the data provider to explicitly allow sharing data with lower edition accounts. Note that this parameter can only be set by the data provider, not the data consumer. Also, setting this parameter to false may reduce the level of security and data protection for the shared data.
References:
* Enable Data Share:Business Critical Account to Lower Edition
* Sharing Is Not Allowed From An Account on BUSINESS CRITICAL Edition to an Account On A Lower Edition
* SQL Execution Error: Sharing is Not Allowed from an Account on BUSINESS CRITICAL Edition to an Account on a Lower Edition
* Snowflake Editions | Snowflake Documentation
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Question 9

Which Snowflake data modeling approach is designed for BI queries?

Correct Answer: B
A star schema is a Snowflake data modeling approach that is designed for BI queries. A star schema is a type of dimensional modeling that organizes data into fact tables and dimension tables. A fact table contains the measures or metrics of the business process, such as sales amount, order quantity, or profit margin. A dimension table contains the attributes or descriptors of the business process, such as product name, customer name, or order date. A star schema is called so because it resembles a star, with one fact table in the center and multiple dimension tables radiating from it. A star schema can improve the performance and simplicity of BI queries by reducing the number of joins, providing fast access to aggregated data, and enabling intuitive query syntax. A star schema can also support various types of analysis, such as trend analysis, slice and dice, drill down, and roll up12.
References:
Snowflake Documentation: Dimensional Modeling
Snowflake Documentation: Star Schema
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Question 10

An Architect runs the following SQL query:

How can this query be interpreted?

Correct Answer: A
* A stage is a named location in Snowflake that can store files for data loading and unloading. A stage can be internal or external, depending on where the files are stored.
* The query in the question uses the LIST function to list the files in a stage named FILEROWS. The function returns a table with various columns, including FILE_ROW_NUMBER, which is the line number of the file in the stage.
* Therefore, the query can be interpreted as listing the files in a stage named FILEROWS and showing the line number of each file in the stage.
References:
* : Stages
* : LIST Function
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