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Snowflake ARA-C01試験は、スノーフレークソリューションの設計と実装の専門知識を実証したい上級スノーフレークアーキテクト向けに設計された認定試験です。この試験は、スノーフレークアーキテクチャ、実装、およびベストプラクティスに関する候補者の知識をテストするように設計されています。この試験に合格することは、スノーフレークの高レベルの技術的専門知識を実証する素晴らしい成果であり、新しいキャリアの機会にドアを開けることができます。
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質問 # 58
A Snowflake Architect is designing a multi-tenant application strategy for an organization in the Snowflake Data Cloud and is considering using an Account Per Tenant strategy.
Which requirements will be addressed with this approach? (Choose two.)
正解：B、C
解説：
Explanation
* An Account Per Tenant strategy means creating a separate Snowflake account for each tenant (customer or business unit) of the multi-tenant application.
* This approach has some advantages and disadvantages compared to other strategies, such as Database Per Tenant or Schema Per Tenant.
* One advantage is that each tenant can have a unique data shape, meaning they can define their own tables, views, and other objects without affecting other tenants. This allows for more flexibility and customization for each tenant. Therefore, option D is correct.
* Another advantage is that storage costs can be optimized, because each tenant can use their own storage credits and manage their own data retention policies. This also reduces the risk of data spillover or cross-tenant access. Therefore, option E is correct.
* However, this approach also has some drawbacks, such as:
* It requires more administrative overhead and complexity to manage multiple accounts and their resources.
* It may not optimize compute costs, because each tenant has to provision their own warehouses and pay for their own compute credits. This may result in underutilization or overprovisioning of compute resources. Therefore, option C is incorrect.
* It may not simplify security and RBAC policies, because each account has to define its own roles, users, and privileges. This may increase the risk of human errors or inconsistencies in security configurations. Therefore, option B is incorrect.
* It may not reduce the number of objects per tenant, because each tenant still has to create their own databases, schemas, and other objects within their account. This mayaffect the performance and scalability of the application. Therefore, option A is incorrect.
References: : Multi-Tenant Application Strategies
質問 # 59
An Architect clones a database and all of its objects, including tasks. After the cloning, the tasks stop running.
Why is this occurring?
正解：A
解説：
When a database is cloned, all of its objects, including tasks, are also cloned. However, cloned tasks are suspended by default and must be manually resumed by using the ALTER TASK command. This is to prevent the cloned tasks from running unexpectedly or interfering with the original tasks. Therefore, the reason why the tasks stop running after the cloning is because they are suspended by default (Option C). Options A, B, and D are not correct because tasks can be cloned, the objects that the tasks reference are also cloned and do not need to be fully qualified, and the Architect does not need to alter the tasks on the cloned database, only resume them. References: The answer can be verified from Snowflake's official documentation on cloning and tasks available on their website. Here are some relevant links:
* Cloning Objects | Snowflake Documentation
* Tasks | Snowflake Documentation
* ALTER TASK | Snowflake Documentation
質問 # 60
A retailer's enterprise data organization is exploring the use of Data Vault 2.0 to model its data lake solution.
A Snowflake Architect has been asked to provide recommendations for using Data Vault 2.0 on Snowflake.
What should the Architect tell the data organization? (Select TWO).
正解：A、E
解説：
Data Vault 2.0 on Snowflake supports the HASH_DIFF concept for change data capture, which is a method to detect changes in the data by comparing the hash values of the records. Additionally, Snowflake's multi-table insert feature allows for the loading of multiple PIT tables in parallel from a single join query, which can significantly streamline the data loading process and improve performance1.
References =
*Snowflake's documentation on multi-table inserts1
*Blog post on optimizing Data Vault architecture on Snowflake2
質問 # 61
What is a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka?
正解：B
解説：
According to the SnowPro Advanced: Architect documents and learning resources, a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka is that the Connector creates and manages its own stage, file format, and pipe objects. The stage is an internal stage that is used to store the data files from the Kafka topics. The file format is a JSON or Avro file format that is used to parse the data files. The pipe is a Snowpipe object that is used to load the data files into the Snowflake table. The Connector automatically creates and configures these objects based on the Kafka configuration properties, and handles the cleanup and maintenance of these objects1.
The other options are incorrect because they are not characteristics of loading data into Snowflake using the Snowflake Connector for Kafka. Option A is incorrect because the Connector works in Snowflake regions that use any cloud infrastructure, not just AWS. The Connector supports AWS, Azure, and Google Cloud platforms, and can load data across different regions and cloud platforms using data replication2. Option B is incorrect because the Connector does not work with all file formats, only JSON and Avro. The Connector expects the data in the Kafka topics to be in JSON or Avro format, and parses the data accordingly. Other file formats, such as text, ORC, Parquet, or XML, are not supported by the Connector3. Option D is incorrect because loads using the Connector do not have lower latency than Snowpipe, and do not ingest data in real time. The Connector uses Snowpipe to load data into Snowflake, and inherits the same latency and performance characteristics of Snowpipe. The Connector does not provide real-time ingestion, but near real-time ingestion, depending on the frequency and size of the data files4. References: Installing and Configuring the Kafka Connector | Snowflake Documentation, Sharing Data Across Regions and Cloud Platforms | Snowflake Documentation, Overview of the Kafka Connector | Snowflake Documentation, Using Snowflake Connector for Kafka With Snowpipe Streaming | Snowflake Documentation
質問 # 62
Why does a conditional multi-table insert option support the Data Vault data model?
正解：C
解説：
The Data Vault modeling approach separates data into hubs (business keys), links, and satellites, often requiring simultaneous insertion of related records derived from the same source dataset. Snowflake's conditional multi-table INSERT enables a single source query to populate multiple target tables in parallel based on conditional logic. This capability aligns well with Data Vault patterns, where hubs and satellites are typically loaded together from the same staging data.
By inserting into hubs and satellites in parallel using surrogate keys (Answer A), architects ensure consistency, atomicity, and efficient processing without re-scanning source data multiple times. This approach reduces compute usage and simplifies ETL logic, which is particularly valuable in large-scale, near-real-time ingestion pipelines.
Options involving dimensions and facts relate more closely to star schema modeling, not Data Vault.
Sequential insertion is also less efficient and not the defining advantage of conditional multi-table inserts. For SnowPro Architect candidates, this question emphasizes understanding how Snowflake SQL features support modern data modeling techniques such as Data Vault.
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質問 # 63
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ARA-C01日本語試験対策: https://www.xhs1991.com/ARA-C01.html
無料でクラウドストレージから最新のXhs1991 ARA-C01 PDFダンプをダウンロードする：https://drive.google.com/open?id=1pnk0WZqSOwqfmJU037oUGeNr556l3Ylr