[2025] Verified ARA-C01 Dumps Q&As - 1 Year Free & Quickly Updates [Q29-Q53]

[2025] Verified ARA-C01 Dumps Q&As - 1 Year Free & Quickly Updates

Latest 2025 Realistic Verified ARA-C01 Dumps - 100% Free ARA-C01 Exam Dumps

Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Certification Exam is designed to test the ability of experienced Snowflake architects to design and implement complex Snowflake solutions. SnowPro Advanced Architect Certification certification exam is intended for professionals who have extensive experience in architecting Snowflake solutions and want to demonstrate their expertise and proficiency. ARA-C01 exam assesses the candidate's ability to design, plan, and implement Snowflake solutions in a variety of scenarios.

Snowflake ARA-C01 exam covers a wide range of advanced topics related to Snowflake architecture, including data modeling, security, performance tuning, and data integration. Candidates are expected to have a deep understanding of Snowflake’s features and functionality, as well as the ability to apply this knowledge to real-world scenarios.

 

NEW QUESTION # 29
When activating Tri-Secret Secure in a hierarchical encryption model in a Snowflake account, at what level is the customer-managed key used?

• A. At the micro-partition level
• B. At the table level (TMK)
• C. At the account level (AMK)
• D. At the root level (HSM)

Answer: B

NEW QUESTION # 30
In this scenarios, files are constantly getting ingested in an external stage, the files are between 1 and 4 MB. You want to load the data immediately into a table without any human intervention.
What will you use?

• A. Use Snowpipe with auto ingest
• B. Use Snowpipe rest APIs
• C. Create a materialize view on the external stage

Answer: A

NEW QUESTION # 31
A company needs to share its product catalog data with one of its partners. The product catalog data is stored in two database tables: product_category, and product_details. Both tables can be joined by the product_id column. Data access should be governed, and only the partner should have access to the records.
The partner is not a Snowflake customer. The partner uses Amazon S3 for cloud storage.
Which design will be the MOST cost-effective and secure, while using the required Snowflake features?

• A. Create a reader account for the partner and share the data sets as secure views.
• B. Publish product_category and product_details data sets on the Snowflake Marketplace.
• C. Use Secure Data Sharing with an S3 bucket as a destination.
• D. Create a database user for the partner and give them access to the required data sets.

Answer: A

Explanation:
A reader account is a type of Snowflake account that allows external users to access data shared by a provider account without being a Snowflake customer. A reader account can be created and managed by the provider account, and can use the Snowflake web interface or JDBC/ODBC drivers to query the shared data. A reader account is billed to the provider account based on the credits consumed by the queries1. A secure view is a type of view that applies row-level security filters to the underlying tables, and masks the data that is not accessible to the user. A secure view can be shared with a reader account to provide granular and governed access to the data2. In this scenario, creating a reader account for the partner and sharing the data sets as secure views would be the most cost-effective and secure design, while using the required Snowflake features, because:
* It would avoid the data transfer and storage costs of using an S3 bucket as a destination, and the potential security risks of exposing the data to unauthorized access or modification.
* It would avoid the complexity and overhead of publishing the data sets on the Snowflake Marketplace, and the potential loss of control over the data ownership and pricing.
* It would avoid the need to create a database user for the partner and grant them access to the required data sets, which would require the partner to have a Snowflake account and consume the provider's resources.
References:
* Reader Accounts
* Secure Views

NEW QUESTION # 32
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. Grant modify permissions on the share.
• B. Create a table stream on the shared table.
• C. Create a table from the shared database.
• D. Create additional views inside the shared database.
• E. Clone a table from a share.

Answer: D,E

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 # 33
A company wants to Integrate its main enterprise identity provider with federated authentication with Snowflake.
The authentication integration has been configured and roles have been created in Snowflake. However, the users are not automatically appearing in Snowflake when created and their group membership is not reflected in their assigned rotes.
How can the missing functionality be enabled with the LEAST amount of operational overhead?

• A. SCIM must be enabled between the identity provider and Snowflake. Once both are synchronized through SCIM, their groups will get created as group accounts in Snowflake and the proper roles can be granted.
• B. OAuth must be configured between the identity provider and Snowflake. Then the authorization server must be configured with the right mapping of users and roles.
• C. OAuth must be configured between the identity provider and Snowflake. Then the authorization server must be configured with the right mapping of users, and the resource server must be configured with the right mapping of role assignment.
• D. SCIM must be enabled between the identity provider and Snowflake. Once both are synchronized through SCIM. users will automatically get created and their group membership will be reflected as roles In Snowflake.

Answer: D

Explanation:
The best way to integrate an enterprise identity provider with federated authentication and enable automatic user creation and role assignment in Snowflake is to use SCIM (System for Cross-domain Identity Management). SCIM allows Snowflake to synchronize with the identity provider and create users and groups based on the information provided by the identity provider. The groups are mapped to roles in Snowflake, and the users are assigned the roles based on their group membership. This way, the identity provider remains the source of truth for user and group management, and Snowflake automatically reflects the changes without manual intervention. The other options are either incorrect or incomplete, as they involve using OAuth, which is a protocol for authorization, not authentication or user provisioning, and require additional configuration of authorization and resource servers.

NEW QUESTION # 34
A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.
The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.
What step can be taken to improve the pruning of the reporting tables?

• A. Eliminate the use of Snowpipe and load the files into internal stages using PUT commands.
• B. Increase the size of the virtual warehouse to a size 5X-Large.
• C. Create larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.
• D. Use an ORDER BY <cluster_key (s) > command to load the reporting tables.

Answer: D

Explanation:
Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.
References =
*Snowflake Documentation on micro-partitions and data clustering2
*Community article on recognizing unsatisfactory pruning and improving it1

NEW QUESTION # 35
Multi-cluster warehouses are best utilized for

• A. Improving the performance of data loading
• B. Scaling resources to improve concurrency for users/queries
• C. Improving the performance of slow-running queries

Answer: B

NEW QUESTION # 36
What Snowflake features should be leveraged when modeling using Data Vault?

• A. Scaling up the virtual warehouses will support parallel processing of new source loads
• B. Snowflake's ability to hash keys so that hash key joins can run faster than integer joins
• C. Data needs to be pre-partitioned to obtain a superior data access performance
• D. Snowflake's support of multi-table inserts into the data model's Data Vault tables

Answer: A,D

Explanation:
These two features are relevant for modeling using Data Vault on Snowflake. Data Vault is a data modeling approach that organizes data into hubs, links, and satellites. Data Vault is designed to enable high scalability, flexibility, and performance for data integration and analytics. Snowflake is a cloud data platform that supports various data modeling techniques, including Data Vault. Snowflake provides some features that can enhance the Data Vault modeling, such as:
Snowflake's support of multi-table inserts into the data model's Data Vault tables. Multi-table inserts (MTI) are a feature that allows inserting data from a single query into multiple tables in a single DML statement. MTI can improve the performance and efficiency of loading data into Data Vault tables, especially for real-time or near-real-time data integration. MTI can also reduce the complexity and maintenance of the loading code, as well as the data duplication and latency12.
Scaling up the virtual warehouses will support parallel processing of new source loads. Virtual warehouses are a feature that allows provisioning compute resources on demand for data processing. Virtual warehouses can be scaled up or down by changing the size of the warehouse, which determines the number of servers in the warehouse. Scaling up the virtual warehouses can improve the performance and concurrency of processing new source loads into Data Vault tables, especially for large or complex data sets. Scaling up the virtual warehouses can also leverage the parallelism and distribution of Snowflake's architecture, which can optimize the data loading and querying34.
Reference:
Snowflake Documentation: Multi-table Inserts
Snowflake Blog: Tips for Optimizing the Data Vault Architecture on Snowflake Snowflake Documentation: Virtual Warehouses Snowflake Blog: Building a Real-Time Data Vault in Snowflake

NEW QUESTION # 37
What are purposes for creating a storage integration? (Choose three.)

• A. Control access to Snowflake data using a master encryption key that is maintained in the cloud provider's key management service.
• B. Avoid supplying credentials when creating a stage or when loading or unloading data.
• C. Create private VPC endpoints that allow direct, secure connectivity between VPCs without traversing the public internet.
• D. Store a generated identity and access management (IAM) entity for an external cloud provider regardless of the cloud provider that hosts the Snowflake account.
• E. Manage credentials from multiple cloud providers in one single Snowflake object.
• F. Support multiple external stages using one single Snowflake object.

Answer: B,D,F

Explanation:
* 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

NEW QUESTION # 38
A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.
The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.
What step can be taken to improve the pruning of the reporting tables?

• A. Eliminate the use of Snowpipe and load the files into internal stages using PUT commands.
• B. Increase the size of the virtual warehouse to a size 5X-Large.
• C. Create larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.
• D. Use an ORDER BY <cluster_key (s) > command to load the reporting tables.

Answer: D

Explanation:
Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.
Reference =
* Snowflake Documentation on micro-partitions and data clustering2
* Community article on recognizing unsatisfactory pruning and improving it1

NEW QUESTION # 39
A company's client application supports multiple authentication methods, and is using Okta.
What is the best practice recommendation for the order of priority when applications authenticate to Snowflake?

• A. 1) Password
  2) Key Pair Authentication, mostly used for production environment users
  3) Okta native authentication
  4) OAuth (either Snowflake OAuth or External OAuth)
  5) External browser, SSO
• B. 1) OAuth (either Snowflake OAuth or External OAuth)
  2) External browser
  3) Okta native authentication
  4) Key Pair Authentication, mostly used for service account users
  5) Password
• C. 1) Okta native authentication
  2) Key Pair Authentication, mostly used for production environment users
  3) Password
  4) OAuth (either Snowflake OAuth or External OAuth)
  5) External browser, SSO
• D. 1) External browser, SSO
  2) Key Pair Authentication, mostly used for development environment users
  3) Okta native authentication
  4) OAuth (ether Snowflake OAuth or External OAuth)
  5) Password

Answer: B

Explanation:
This is the best practice recommendation for the order of priority when applications authenticate to Snowflake, according to the Snowflake documentation and the web search results. Authentication is the process of verifying the identity of a user or application that connects to Snowflake. Snowflake supports multiple authentication methods, each with different advantages and disadvantages. The recommended order of priority is based on the following factors:
* Security: The authentication method should provide a high level of security and protection against unauthorized access or data breaches. The authentication method should also support multi-factor authentication (MFA) or single sign-on (SSO) for additional security.
* Convenience: The authentication method should provide a smooth and easy user experience, without requiring complex or manual steps. The authentication method should also support seamless integration with external identity providers or applications.
* Flexibility: The authentication method should provide a range of options and features to suit different use cases and scenarios. The authentication method should also support customization and configuration to meet specific requirements.
Based on these factors, the recommended order of priority is:
* OAuth (either Snowflake OAuth or External OAuth): OAuth is an open standard for authorization that allows applications to access Snowflake resources on behalf of a user, without exposing the user's credentials. OAuth provides a high level of security, convenience, and flexibility, as it supports MFA,
* SSO, token-based authentication, and various grant types and scopes. OAuth can be implemented using either Snowflake OAuth or External OAuth, depending on the identity provider and the application12.
* External browser: External browser is an authentication method that allows users to log in to Snowflake using a web browser and an external identity provider, such as Okta, Azure AD, or Ping Identity.
External browser provides a high level of security and convenience, as it supports MFA, SSO, and federated authentication. External browser also provides a consistent user interface and experience across different platforms and devices34.
* Okta native authentication: Okta native authentication is an authentication method that allows users to log in to Snowflake using Okta as the identity provider, without using a web browser. Okta native authentication provides a high level of security and convenience, as it supports MFA, SSO, and federated authentication. Okta native authentication also provides a native user interface and experience for Okta users, and supports various Okta features, such as password policies and user management56.
* Key Pair Authentication: Key Pair Authentication is an authentication method that allows users to log in to Snowflake using a public-private key pair, without using a password. Key Pair Authentication provides a high level of security, as it relies on asymmetric encryption and digital signatures. Key Pair Authentication also provides a flexible and customizable authentication option, as it supports various key formats, algorithms, and expiration times. Key Pair Authentication is mostly used for service account users, such as applications or scripts that connect to Snowflake programmatically7 .
* Password: Password is the simplest and most basic authentication method that allows users to log in to Snowflake using a username and password. Password provides a low level of security, as it relies on symmetric encryption and is vulnerable to brute force attacks or phishing. Password also provides a low level of convenience and flexibility, as it requires manual input and management, and does not support MFA or SSO. Password is the least recommended authentication method, and should be used only as a last resort or for testing purposes .
References:
* Snowflake Documentation: Snowflake OAuth
* Snowflake Documentation: External OAuth
* Snowflake Documentation: External Browser Authentication
* Snowflake Blog: How to Use External Browser Authentication with Snowflake
* Snowflake Documentation: Okta Native Authentication
* Snowflake Blog: How to Use Okta Native Authentication with Snowflake
* Snowflake Documentation: Key Pair Authentication
* [Snowflake Blog: How to Use Key Pair Authentication with Snowflake]
* [Snowflake Documentation: Password Authentication]
* [Snowflake Blog: How to Use Password Authentication with Snowflake]

NEW QUESTION # 40
A user has activated primary and secondary roles for a session.
What operation is the user prohibited from using as part of SQL actions in Snowflake using the secondary role?

• A. Truncate
• B. Create
• C. Insert
• D. Delete

Answer: B

Explanation:
In Snowflake, when a user activates a secondary role during a session, certain privileges associated with DDL (Data Definition Language) operations are restricted. The CREATE statement, which falls under DDL operations, cannot be executed using a secondary role. This limitation is designed to enforce role-based access control and ensure that schema modifications are managed carefully, typically reserved for primary roles that have explicit permissions to modify database structures.References: Snowflake's security and access control documentation specifying the limitations and capabilities of primary versus secondary roles in session management.

NEW QUESTION # 41
A DevOps team has a requirement for recovery of staging tables used in a complex set of data pipelines. The staging tables are all located in the same staging schem a. One of the requirements is to have online recovery of data on a rolling 7-day basis.
After setting up the DATA_RETENTION_TIME_IN_DAYS at the database level, certain tables remain unrecoverable past 1 day.
What would cause this to occur? (Choose two.)

• A. The DevOps role should be granted ALLOW_RECOVERY privilege on the staging schema.
• B. The staging schema has not been setup for MANAGED ACCESS.
• C. The DATA_RETENTION_TIME_IN_DAYS for the staging schema has been set to 1 day.
• D. The tables exceed the 1 TB limit for data recovery.
• E. The staging tables are of the TRANSIENT type.

Answer: C,E

NEW QUESTION # 42
How is the change of local time due to daylight savings time handled in Snowflake tasks? (Choose two.)

• A. A task schedule will follow only the specified time and will fail to handle lost or duplicated hours.
• B. A task will move to a suspended state during the daylight savings time change.
• C. A task scheduled in a UTC-based schedule will have no issues with the time changes.
• D. A frequent task execution schedule like minutes may not cause a problem, but will affect the task history.
• E. Task schedules can be designed to follow specified or local time zones to accommodate the time changes.

Answer: C,E

Explanation:
Explanation
According to the Snowflake documentation1 and the web search results2, these two statements are true about how the change of local time due to daylight savings time is handled in Snowflake tasks. A task is a feature that allows scheduling and executing SQL statements or stored procedures in Snowflake. A task can be scheduled using a cron expression that specifies the frequency and time zone of the task execution.
* A task scheduled in a UTC-based schedule will have no issues with the time changes. UTC is a universal time standard that does not observe daylight savings time. Therefore, a task that uses UTC as the time zone will run at the same time throughout the year, regardless of the local time changes1.
* Task schedules can be designed to follow specified or local time zones to accommodate the time changes. Snowflake supports using any valid IANA time zone identifier in the cron expression for a task. This allows the task to run according to the local time of the specified time zone, which may include daylight savings time adjustments. For example, a task that uses Europe/London as the time zone will run one hour earlier or later when the local time switches between GMT and BST12.
References:
* Snowflake Documentation: Scheduling Tasks
* Snowflake Community: Do the timezones used in scheduling tasks in Snowflake adhere to daylight savings?

NEW QUESTION # 43
What step will improve the performance of queries executed against an external table?

• A. Shorten the names of the source files.
• B. Use an internal stage instead of an external stage to store the source files.
• C. Convert the source files' character encoding to UTF-8.
• D. Partition the external table.

Answer: D

NEW QUESTION # 44
An Architect clones a database and all of its objects, including tasks. After the cloning, the tasks stop running.
Why is this occurring?

• A. Cloned tasks are suspended by default and must be manually resumed.
• B. Tasks cannot be cloned.
• C. The objects that the tasks reference are not fully qualified.
• D. The Architect has insufficient privileges to alter tasks on the cloned database.

Answer: A

NEW QUESTION # 45
Based on the Snowflake object hierarchy, what securable objects belong directly to a Snowflake account?
(Select THREE).

• A. Role
• B. Stage
• C. Schema
• D. Warehouse
• E. Database
• F. Table

Answer: A,D,E

Explanation:
* A securable object is an entity to which access can be granted in Snowflake. Securable objects include databases, schemas, tables, views, stages, pipes, functions, procedures, sequences, tasks, streams, roles, warehouses, and shares1.
* The Snowflake object hierarchy is a logical structure that organizes the securable objects in a nested manner. The top-most container is the account, which contains all the databases, roles, and warehouses for the customer organization. Each database contains schemas, which in turn contain tables, views, stages, pipes, functions, procedures, sequences, tasks, and streams. Each role can be granted privileges on other roles or securable objects. Each warehouse can be used to execute queries on securable objects2.
* Based on the Snowflake object hierarchy, the securable objects that belong directly to a Snowflake account are databases, roles, and warehouses. These objects are created and managed at the account level, and do not depend on any other securable object. The other options are not correct because:
* Schemas belong to databases, not to accounts. A schema must be created within an existing database3.
* Tables belong to schemas, not to accounts. A table must be created within an existing schema4.
* Stages belong to schemas or tables, not to accounts. A stage must be created within an existing
* schema or table.
References:
* 1: Overview of Access Control | Snowflake Documentation
* 2: Securable Objects | Snowflake Documentation
* 3: CREATE SCHEMA | Snowflake Documentation
* 4: CREATE TABLE | Snowflake Documentation
* [5]: CREATE STAGE | Snowflake Documentation

NEW QUESTION # 46
What is the best practice to follow when calling the SNOWPIPE REST API loadHistoryScan

• A. Reading the last 10 minutes of history every 8 minutes
• B. Read the last 7 days of history every hour
• C. Read the last 24 hours of history every minute

Answer: A

NEW QUESTION # 47
Which Snowflake architecture recommendation needs multiple Snowflake accounts for implementation?

• A. Enable zero-copy cloning among the development, test, and production environments.
• B. Enable separation of the development, test, and production environments.
• C. Enable a disaster recovery strategy across multiple cloud providers.
• D. Create external stages pointing to cloud providers and regions other than the region hosting the Snowflake account.

Answer: B

Explanation:
The Snowflake architecture recommendation that necessitates multiple Snowflake accounts for implementation is the separation of development, test, and production environments. This approach, known as Account per Tenant (APT), isolates tenants into separate Snowflake accounts, ensuring dedicated resources and security isolation12.
References
*Snowflake's white paper on "Design Patterns for Building Multi-Tenant Applications on Snowflake" discusses the APT model and its requirement for separate Snowflake accounts for each tenant1.
*Snowflake Documentation on Secure Data Sharing, which mentions the possibility of sharing data across multiple accounts3.

NEW QUESTION # 48
An Architect with the ORGADMIN role wants to change a Snowflake account from an Enterprise edition to a Business Critical edition.
How should this be accomplished?

• A. Failover to a new account in the same region and specify the new account's edition upon creation.
• B. Contact Snowflake Support and request that the account's edition be changed.
• C. Run an ALTER ACCOUNT command and create a tag of EDITION and set the tag to Business Critical.
• D. Use the account's ACCOUNTADMIN role to change the edition.

Answer: B

Explanation:
To change the edition of a Snowflake account, an organization administrator (ORGADMIN) cannot directly alter the account settings through SQL commands or the Snowflake interface. The proper procedure is to contact Snowflake Support to request an edition change for the account. This ensures that the change is managed correctly and aligns with Snowflake's operational protocols.
References: This process is outlined in the Snowflake documentation, which specifies that changes to an account's edition should be facilitated through Snowflake Support1.

NEW QUESTION # 49
The IT Security team has identified that there is an ongoing credential stuffing attack on many of their organization's system.
What is the BEST way to find recent and ongoing login attempts to Snowflake?

• A. View the History tab in the Snowflake UI and set up a filter for SQL text that contains the text
  "LOGIN".
• B. Query the LOGIN_HISTORY view in the ACCOUNT_USAGE schema in the SNOWFLAKE database.
• C. View the Users section in the Account tab in the Snowflake UI and review the last login column.
• D. Call the LOGIN_HISTORY Information Schema table function.

Answer: B

Explanation:
This view can be used to query login attempts by Snowflake users within the last 365 days (1 year). It provides information such as the event timestamp, the user name, the client IP, the authentication method, the success or failure status, and the error code or message if the login attempt was unsuccessful. By querying this view, the IT Security team can identify any suspicious or malicious login attempts to Snowflake and take appropriate actions to prevent credential stuffing attacks1. The other options are not the best ways to find recent and ongoing login attempts to Snowflake. Option A is incorrect because the LOGIN_HISTORY Information Schema table function only returns login events within the last 7 days, which may not be sufficient to detect credential stuffing attacks that span a longer period of time2. Option C is incorrect because the History tab in the Snowflake UI only shows the queries executed by the current user or role, not the login events of other users or roles3. Option D is incorrect because the Users section in the Account tab in the Snowflake UI only shows the last login time for each user, not the details of the login attempts or the failures.

NEW QUESTION # 50
Snowflake includes administration settings for resource consumption in order to

• A. Help control costs associated with unexpected credit usage of data
• B. Manage access to data warehouses for specific users
• C. Maintain data availability

Answer: A

NEW QUESTION # 51
While creating a clustering key, what is the recommendation for maximum number of columns that you can include as part of the key?

• A. Unlimited
• B. Not more than 16
• C. 0
• D. 3 to 4

Answer: D

NEW QUESTION # 52
An Architect uses COPY INTO with the ON_ERROR=SKIP_FILE option to bulk load CSV files into a table called TABLEA, using its table stage. One file named file5.csv fails to load. The Architect fixes the file and re-loads it to the stage with the exact same file name it had previously.
Which commands should the Architect use to load only file5.csv file from the stage? (Choose two.)

• A. COPY INTO tablea FROM @%tablea;
• B. COPY INTO tablea FROM @%tablea NEW_FILES_ONLY = TRUE;
• C. COPY INTO tablea FROM @%tablea FORCE = TRUE;
• D. COPY INTO tablea FROM @%tablea MERGE = TRUE;
• E. COPY INTO tablea FROM @%tablea RETURN_FAILED_ONLY = TRUE;
• F. COPY INTO tablea FROM @%tablea FILES = ('file5.csv');

Answer: A,F

Explanation:
Option A (RETURN_FAILED_ONLY) will only load files that previously failed to load. Since file5.csv already exists in the stage with the same name, it will not be considered a new file and will not be loaded.
Option D (FORCE) will overwrite any existing data in the table. This is not desired as we only want to load the data from file5.csv.
Option E (NEW_FILES_ONLY) will only load files that have been added to the stage since the last COPY command. This will not work because file5.csv was already in the stage before it was fixed.
Option F (MERGE) is used to merge data from a stage into an existing table, creating new rows for any data not already present. This is not needed in this case as we simply want to load the data from file5.csv.
Therefore, the architect can use either COPY INTO tablea FROM @%tablea or COPY INTO tablea FROM @%tablea FILES = ('file5.csv') to load only file5.csv from the stage. Both options will load the data from the specified file without overwriting any existing data or requiring additional configuration

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