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  1. Home
  2. Snowflake Certification
  3. ARA-C01 Exam
  4. Snowflake.ARA-C01.v2026-04-11.q236 Dumps
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Question 36

What are purposes for creating a storage integration? (Choose three.)

Correct Answer: B,C,D
* A storage integration is a Snowflake object that stores a generated identity and access management (IAM) entity for an external cloud provider, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. This integration allows Snowflake to read data from and write data to an external storage location referenced in an external stage1.
* One purpose of creating a storage integration is to support multiple external stages using one single Snowflake object. An integration can list buckets (and optional paths) that limit the locations users can specify when creating external stages that use the integration. Note that many external stage objects can reference different buckets and paths and use the same storage integration for authentication1.
Therefore, option C is correct.
* Another purpose of creating a storage integration is to avoid supplying credentials when creating a stage or when loading or unloading data. Integrations are named, first-class Snowflake objects that avoid the need for passing explicit cloud provider credentials such as secret keys or access tokens. Integration objects store an IAM user ID, and an administrator in your organization grants the IAM user permissions in the cloud provider account1. Therefore, option D is correct.
* A third purpose of creating a storage integration is to store a generated IAM entity for an external cloud provider regardless of the cloud provider that hosts the Snowflake account. For example, you can create a storage integration for Amazon S3 even if your Snowflake account is hosted on Azure or Google Cloud Platform. This allows you to access data across different cloud platforms using Snowflake1.
Therefore, option B is correct.
* Option A is incorrect, because creating a storage integration does not control access to Snowflake data using a master encryption key. Snowflake encrypts all data using a hierarchical key model, and the master encryption key is managed by Snowflake or by the customer using a cloud provider's key management service. This is independent of the storage integration feature2.
* Option E is incorrect, because creating a storage integration does not create private VPC endpoints.
Private VPC endpoints are a network configuration option that allow direct, secure connectivity between VPCs without traversing the public internet. This is also independent of the storage integration feature3.
* Option F is incorrect, because creating a storage integration does not manage credentials from multiple cloud providers in one single Snowflake object. A storage integration is specific to one cloud provider, and you need to create separate integrations for each cloud provider you want to access4.
References: : Encryption and Decryption : Private Link for Snowflake : CREATE STORAGE INTEGRATION : Option 1: Configuring a Snowflake Storage Integration to Access Amazon S3
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Question 37

A company is following the Data Mesh principles, including domain separation, and chose one Snowflake account for its data platform.
An Architect created two data domains to produce two data products. The Architect needs a third data domain that will use both of the data products to create an aggregate data product. The read access to the data products will be granted through a separate role.
Based on the Data Mesh principles, how should the third domain be configured to create the aggregate product if it has been granted the two read roles?

Correct Answer: D
In the scenario described, where a third data domain needs access to two existing data products in a Snowflake account structured according to Data Mesh principles, the best approach is to utilize Snowflake's Data Exchange functionality. Option D is correct as it facilitates the sharing and governance of data across different domains efficiently and securely. Data Exchange allows domains to publish and subscribe to live data products, enabling real-time data collaboration and access management in a governed manner. This approach is in line with Data Mesh principles, which advocate for decentralized data ownership and architecture, enhancing agility and scalability across the organization.References:
* Snowflake Documentation on Data Exchange
* Articles on Data Mesh Principles in Data Management
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Question 38

A company has several sites in different regions from which the company wants to ingest data.
Which of the following will enable this type of data ingestion?

Correct Answer: D
This is the correct answer because it allows the company to ingest data from different regions using a storage integration for the external stage. A storage integration is a feature that enables secure and easy access to files in external cloud storage from Snowflake. A storage integration can be used to create an external stage, which is a named location that references the files in the external storage. An external stage can be used to load data into Snowflake tables using the COPY INTO command, or to unload data from Snowflake tables using the COPY INTO LOCATION command. A storage integration can support multiple regions and cloud platforms, as long as the external storage service is compatible with Snowflake12.
Reference:
Snowflake Documentation: Storage Integrations
Snowflake Documentation: External Stages
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Question 39

How can an Architect enable optimal clustering to enhance performance for different access paths on a given table?

Correct Answer: B
According to the SnowPro Advanced: Architect documents and learning resources, the best way to enable optimal clustering to enhance performance for different access paths on a given table is to create multiple materialized views with different cluster keys. A materialized view is a pre-computed result set that is derived from a query on one or more base tables. A materialized view can be clustered by specifying a clustering key, which is a subset of columns or expressions that determines how the data in the materialized view is co-located in micro-partitions. By creating multiple materialized views with different cluster keys, an Architect can optimize the performance of queries that use different access paths on the same base table. For example, if a base table has columns A, B, C, and D, and there are queries that filter on A and B, or on C and D, or on A and C, the Architect can create three materialized views, each with a different cluster key: (A, B), (C, D), and (A, C). This way, each query can leverage the optimal clustering of the corresponding materialized view and achieve faster scan efficiency and better compression.
Reference:
Snowflake Documentation: Materialized Views
Snowflake Learning: Materialized Views
https://www.snowflake.com/blog/using-materialized-views-to-solve-multi-clustering-performance-problems/
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Question 40

An Architect needs to design a data unloading strategy for Snowflake, that will be used with the COPY INTO
<location> command.
Which configuration is valid?

Correct Answer: A
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