2025 ARA-C01 NEW STUDY GUIDE | VALID SNOWPRO ADVANCED ARCHITECT CERTIFICATION 100% FREE AUTHENTIC EXAM HUB

2025 ARA-C01 New Study Guide | Valid SnowPro Advanced Architect Certification 100% Free Authentic Exam Hub

2025 ARA-C01 New Study Guide | Valid SnowPro Advanced Architect Certification 100% Free Authentic Exam Hub

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q162-Q167):

NEW QUESTION # 162
While loading data into a table from stage, which are the valid copyOptions

  • A. SKIP_FILE
  • B. CONTINUE
  • C. ABORT_STATEMENT
  • D. SKIP_FILE_<NUM>
  • E. SKIP_FILE_<NUM>%
  • F. ERROR_STATEMENT

Answer: A,B,C,D,E


NEW QUESTION # 163
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.)

  • A. Tenant data shape may be unique per tenant.
  • B. Compute costs must be optimized.
  • C. There needs to be fewer objects per tenant.
  • D. Storage costs must be optimized.
  • E. Security and Role-Based Access Control (RBAC) policies must be simple to configure.

Answer: A,E

Explanation:
The Account Per Tenant strategy involves creating separate Snowflake accounts for each tenant within the multi-tenant application. This approach offers a number of advantages.
Option B: With separate accounts, each tenant's environment is isolated, making security and RBAC policies simpler to configure and maintain. This is because each account can have its own set of roles and privileges without the risk of cross-tenant access or the complexity of maintaining a highly granular permission model within a shared environment.
Option D: This approach also allows for each tenant to have a unique data shape, meaning that the database schema can be tailored to the specific needs of each tenant without affecting others. This can be essential when tenants have different data models, usage patterns, or application customizations.


NEW QUESTION # 164
A table for IOT devices that measures water usage is created. The table quickly becomes large and contains more than 2 billion rows.

The general query patterns for the table are:
1. DeviceId, lOT_timestamp and Customerld are frequently used in the filter predicate for the select statement
2. The columns City and DeviceManuf acturer are often retrieved
3. There is often a count on Uniqueld
Which field(s) should be used for the clustering key?

  • A. lOT_timestamp
  • B. Uniqueld
  • C. Deviceld and Customerld
  • D. City and DeviceManuf acturer

Answer: C

Explanation:
A clustering key is a subset of columns or expressions that are used to co-locate the data in the same micro-partitions, which are the units of storage in Snowflake. Clustering can improve the performance of queries that filter on the clustering key columns, as it reduces the amount of data that needs to be scanned. The best choice for a clustering key depends on the query patterns and the data distribution in the table. In this case, the columns DeviceId, IOT_timestamp, and CustomerId are frequently used in the filter predicate for the select statement, which means they are good candidates for the clustering key. The columns City and DeviceManufacturer are often retrieved, but not filtered on, so they are not as important for the clustering key.
The column UniqueId is used for counting, but it is not a good choice for the clustering key, as it is likely to have a high cardinality and a uniform distribution, which means it will not help to co-locate the data.
Therefore, the best option is to use DeviceId and CustomerId as the clustering key, as they can help to prune the micro-partitions and speed up the queries. References: Clustering Keys & Clustered Tables, Micro-partitions & Data Clustering, A Complete Guide to Snowflake Clustering


NEW QUESTION # 165
A company is designing its serving layer for data that is in cloud storage. Multiple terabytes of the data will be used for reporting. Some data does not have a clear use case but could be useful for experimental analysis.
This experimentation data changes frequently and is sometimes wiped out and replaced completely in a few days.
The company wants to centralize access control, provide a single point of connection for the end-users, and maintain data governance.
What solution meets these requirements while MINIMIZING costs, administrative effort, and development overhead?

  • A. Import the data used for reporting into a Snowflake schema with native tables. Then create external tables pointing to the cloud storage folders used for the experimentation data. Then create two different roles with grants to the different datasets to match the different user personas, and grant these roles to the corresponding users.
  • B. Import the data used for reporting into a Snowflake schema with native tables. Then create views that have SELECT commands pointing to the cloud storage files for the experimentation data. Then create two different roles to match the different user personas, and grant these roles to the corresponding users.
  • C. Import all the data in cloud storage to be used for reporting into a Snowflake schema with native tables.
    Then create two different roles with grants to the different datasets to match the different user personas, and grant these roles to the corresponding users.
  • D. Import all the data in cloud storage to be used for reporting into a Snowflake schema with native tables.
    Then create a role that has access to this schema and manage access to the data through that role.

Answer: A

Explanation:
The most cost-effective and administratively efficient solution is to use a combination of native and external tables. Native tables for reporting data ensure performance and governance, while external tables allow for flexibility with frequently changing experimental data. Creating roles with specific grants to datasets aligns with the principle of least privilege, centralizing access control and simplifying user management12.
References
*Snowflake Documentation on Optimizing Cost1.
*Snowflake Documentation on Controlling Cost2.


NEW QUESTION # 166
A company has an inbound share set up with eight tables and five secure views. The company plans to make the share part of its production data pipelines.
Which actions can the company take with the inbound share? (Choose two.)

  • A. Create a table stream on the shared table.
  • B. Grant modify permissions on the share.
  • C. Create additional views inside the shared database.
  • D. Clone a table from a share.
  • E. Create a table from the shared database.

Answer: C,D

Explanation:
Explanation
These two actions are possible with an inbound share, according to the Snowflake documentation and the web search results. An inbound share is a share that is created by another Snowflake account (the provider) and imported into your account (the consumer). An inbound share allows you to access the data shared by the provider, but not to modify or delete it. However, you can perform some actions with the inbound share, such as:
* Clone a table from a share. You can create a copy of a table from an inbound share using the CREATE TABLE ... CLONE statement. The clone will contain the same data and metadata as the original table, but it will be independent of the share. You can modify or delete the clone as you wish, but it will not reflect any changes made to the original table by the provider1.
* Create additional views inside the shared database. You can create views on the tables or views from an inbound share using the CREATE VIEW statement. The views will be stored in the shared database, but they will be owned by your account. You can query the views as you would query any other view in your account, but you cannot modify or delete the underlying objects from the share2.
The other actions listed are not possible with an inbound share, because they would require modifying the share or the shared objects, which are read-only for the consumer. You cannot grant modify permissions on the share, create a table from the shared database, or create a table stream on the shared table34.
References:
* Cloning Objects from a Share | Snowflake Documentation
* Creating Views on Shared Data | Snowflake Documentation
* Importing Data from a Share | Snowflake Documentation
* Streams on Shared Tables | Snowflake Documentation


NEW QUESTION # 167
......

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