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Dumps ARA-C01 Free Download - Valid ARA-C01 Test Syllabus

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To be eligible to take the Snowflake ARA-C01 Exam, candidates must have already passed the Snowflake SCA-C01 (SnowPro Core Certification) Exam. The SnowPro Core Certification is the foundation of the SnowPro Certification program and covers the core concepts and skills needed to work with Snowflake. Once a candidate has passed the SnowPro Core Certification, they can then move on to the SnowPro Advanced Architect Certification.

Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Exam is a highly sought-after certification in the field of data warehousing and cloud computing. ARA-C01 exam is designed to test the expertise of professionals in the area of Snowflake architecture and provide them with the necessary accreditation to operate as a SnowPro Advanced Architect.

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Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Certification Exam is an essential credential for professionals who want to demonstrate their expertise in Snowflake architecture. SnowPro Advanced Architect Certification certification program is designed to help professionals stay up-to-date with the latest industry trends and technologies, and it can help them advance their careers by demonstrating their skills and knowledge to potential employers.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q65-Q70):

NEW QUESTION # 65
A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?

A. Create an object for each tenant strategy if row level security is not viable for isolating tenants.
B. Create a multi-tenant table strategy if row level security is not viable for isolating tenants.
C. Create accounts for each tenant in the Snowflake organization.
D. Create an object for each tenant strategy if row level security is viable for isolating tenants.

Answer: C

Explanation:
In a scenario where strong legal isolation is required alongside the need for multi-tenancy, the most effective approach is to create separate accounts for each tenant within the Snowflake organization. This approach ensures complete isolation of data, resources, and management, adhering to strict legal and compliance requirements. Role-Based Access Control (RBAC) further enhances security by allowing granular control over who can access what resources within each account. This solution leverages Snowflake's capabilities for managing multiple accounts under a single organization umbrella, ensuring that each tenant's data and operations are isolated from others.
References:Snowflake documentation on multi-tenancy and account management, part of the SnowPro Advanced: Architect learning path.

NEW QUESTION # 66
The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1) Finance and Vendor Management team members who require reporting and visualization
2) Data Science team members who require access to raw data for ML model development
3) Sales team members who require engineered and protected data for data monetization What Snowflake data modeling approaches will meet these requirements? (Choose two.)

A. Create a set of profile-specific databases that aligns data with usage patterns.
B. Consolidate data in the company's data lake and use EXTERNAL TABLES.
C. Create a raw database for landing and persisting raw data entering the data pipelines.
D. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.
E. Create a single star schema in a single database to support all consumers' requirements.

Answer: A,C

Explanation:
To accommodate the diverse needs of different teams and use cases within a company, a flexible and multi-faceted approach to data modeling is required.
Option B: By creating a raw database for landing and persisting raw data, you ensure that the Data Science team has access to unprocessed data for machine learning model development. This aligns with the best practices of having a staging area or raw data zone in a modern data architecture where raw data is ingested before being transformed or processed for different use cases.
Option C: Having profile-specific databases means creating targeted databases that are designed to meet the specific requirements of each user profile or team within the company. For the Finance and Vendor Management teams, the data can be structured and optimized for reporting and visualization. For the Sales team, the database can include engineered and protected data that is suitable for data monetization efforts. This strategy not only aligns data with usage patterns but also helps in managing data access and security policies effectively.

NEW QUESTION # 67
What transformations are supported in the below SQL statement? (Select THREE).
CREATE PIPE ... AS COPY ... FROM (...)

A. Columns can be omitted.
B. Columns can be reordered.
C. Incoming data can be joined with other tables.
D. The ON ERROR - ABORT statement command can be used.
E. Type casts are supported.
F. Data can be filtered by an optional where clause.

Answer: A,B,F

Explanation:
* The SQL statement is a command for creating a pipe in Snowflake, which is an object that defines the COPY INTO <table> statement used by Snowpipe to load data from an ingestion queue into tables1. The statement uses a subquery in the FROM clause to transform the data from the staged files before loading it into the table2.
* The transformations supported in the subquery are as follows2:
* Data can be filtered by an optional WHERE clause, which specifies a condition that must be satisfied by the rows returned by the subquery. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable
from (
select * from @mystage
where col1 = 'A' and col2 > 10
);
* Columns can be reordered, which means changing the order of the columns in the subquery to match the order of the columns in the target table. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2, col3)
from (
select col3, col1, col2 from @mystage
);
* Columns can be omitted, which means excluding some columns from the subquery that are not needed in the target table. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2)
from (
select col1, col2 from @mystage
);
* The other options are not supported in the subquery because2:
* Type casts are not supported, which means changing the data type of a column in the subquery.
For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2)
from (
select col1::date, col2 from @mystage
);
* Incoming data can not be joined with other tables, which means combining the data from the staged files with the data from another table in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2, col3)
from (
select s.col1, s.col2, t.col3 from @mystage s
join othertable t on s.col1 = t.col1
);
* The ON ERROR - ABORT statement command can not be used, which means aborting the entire load operation if any error occurs. This command can only be used in the COPY INTO <table> statement, not in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable
from (
select * from @mystage
on error abort
);
References:
* 1: CREATE PIPE | Snowflake Documentation
* 2: Transforming Data During a Load | Snowflake Documentation

NEW QUESTION # 68
What integration object should be used to place restrictions on where data may be exported?

A. API integration
B. Security integration
C. Storage integration
D. Stage integration

Answer: C

Explanation:
In Snowflake, a storage integration is used to define and configure external cloud storage that Snowflake will interact with. This includes specifying security policies for access control. One of the main features of storage integrations is the ability to set restrictions on where data may be exported. This is done by binding the storage integration to specific cloud storage locations, thereby ensuring that Snowflake can only access those locations. It helps to maintain control over the data and complies with data governance and security policies by preventing unauthorized data exports to unspecified locations.

NEW QUESTION # 69
Which of the following are characteristics of Snowflake's parameter hierarchy?

A. Table parameters override virtual warehouse parameters.
B. Virtual warehouse parameters override user parameters.
C. Schema parameters override account parameters.
D. Session parameters override virtual warehouse parameters.

Answer: D

NEW QUESTION # 70
......

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