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Snowflake ARA-C01 certification exam consists of 60 multiple-choice questions and has a time limit of 120 minutes. ARA-C01 exam is administered online and can be taken from anywhere in the world. The passing score for the exam is 80%, and individuals who pass the exam will receive the SnowPro Advanced Architect Certification. SnowPro Advanced Architect Certification certification is recognized globally and demonstrates that the holder has the skills and knowledge to design and deploy complex Snowflake solutions that meet the needs of their organization. The SnowPro Advanced Architect Certification is a valuable credential for data architects, data engineers, and data analysts who work with Snowflake and want to advance their careers in the field of data management and analytics.
NEW QUESTION # 39
Search optimization does not support Materialized views and External Tables
- A. TRUE
- B. FALSE
Answer: A
NEW QUESTION # 40
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 root level (HSM)
- D. At the account level (AMK)
Answer: D
Explanation:
Tri-Secret Secure is a feature that allows customers to use their own key, called the customer-managed key (CMK), in addition to the Snowflake-managed key, to create a composite master key that encrypts the data in Snowflake. The composite master key is also known as the account master key (AMK), as it is unique for each account and encrypts the table master keys (TMKs) that encrypt the file keys that encrypt the data files. The customer-managed key is used at the account level, not at the root level, the table level, or the micro-partition level. The root level is protected by a hardware security module (HSM), the table level is protected by the TMKs, and the micro-partition level is protected by the file keys12. References:
* Understanding Encryption Key Management in Snowflake
* Tri-Secret Secure FAQ for Snowflake on AWS
NEW QUESTION # 41
An Architect on a new project has been asked to design an architecture that meets Snowflake security, compliance, and governance requirements as follows:
1) Use Tri-Secret Secure in Snowflake
2) Share some information stored in a view with another Snowflake customer
3) Hide portions of sensitive information from some columns
4) Use zero-copy cloning to refresh the non-production environment from the production environment To meet these requirements, which design elements must be implemented? (Choose three.)
- A. Use the Enterprise edition of Snowflake.
- B. Create a secure view.
- C. Define row access policies.
- D. Use Dynamic Data Masking.
- E. Create a materialized view.
- F. Use the Business-Critical edition of Snowflake.
Answer: B,D,F
Explanation:
These three design elements are required to meet the security, compliance, and governance requirements for the project.
To use Tri-Secret Secure in Snowflake, the Business Critical edition of Snowflake is required. This edition provides enhanced data protection features, such as customer-managed encryption keys, that are not available in lower editions. Tri-Secret Secure is a feature that combines a Snowflake-maintained key and a customer-managed key to create a composite master key to encrypt the data in Snowflake1.
To share some information stored in a view with another Snowflake customer, a secure view is recommended. A secure view is a view that hides the underlying data and the view definition from unauthorized users. Only the owner of the view and the users who are granted the owner's role can see the view definition and the data in the base tables of the view2. A secure view can be shared with another Snowflake account using a data share3.
To hide portions of sensitive information from some columns, Dynamic Data Masking can be used. Dynamic Data Masking is a feature that allows applying masking policies to columns to selectively mask plain-text data at query time. Depending on the masking policy conditions and the user's role, the data can be fully or partially masked, or shown as plain-text4.
NEW QUESTION # 42
An Architect needs to automate the daily Import of two files from an external stage into Snowflake. One file has Parquet-formatted data, the other has CSV-formatted data.
How should the data be joined and aggregated to produce a final result set?
- A. Use Snowpipe to ingest the two files, then create a materialized view to produce the final result set.
- B. Create a task using Snowflake scripting that will import the files, and then call a User-Defined Function (UDF) to produce the final result set.
- C. Create a materialized view to read, Join, and aggregate the data directly from the external stage, and use the view to produce the final result set
- D. Create a JavaScript stored procedure to read. join, and aggregate the data directly from the external stage, and then store the results in a table.
Answer: B
Explanation:
According to the Snowflake documentation, tasks are objects that enable scheduling and execution of SQL statements or JavaScript user-defined functions (UDFs) in Snowflake. Tasks can be used to automate data loading, transformation, and maintenance operations. Snowflake scripting is a feature that allows writing procedural logic using SQL statements and JavaScript UDFs. Snowflake scripting can be used to create complex workflows and orchestrate tasks. Therefore, the best option to automate the daily import of two files from an external stage into Snowflake, join and aggregate the data, and produce a final result set is to create a task using Snowflake scripting that will import the files using the COPY INTO command, and then call a UDF to perform the join and aggregation logic. The UDF can return a table or a variant value as the final result set. Reference:
Tasks
Snowflake Scripting
User-Defined Functions
NEW QUESTION # 43
Schema owner can grant object privileges in a regular schema
- A. FALSE
- B. TRUE
Answer: A
NEW QUESTION # 44
Which system functions does Snowflake provide to monitor clustering information within a table (Choose two.)
- A. SYSTEM$CLUSTERING_KEYS
- B. SYSTEM$CLUSTERING_INFORMATION
- C. SYSTEM$CLUSTERING_PERCENT
- D. SYSTEM$CLUSTERING_DEPTH
- E. SYSTEM$CLUSTERING_USAGE
Answer: B,D
Explanation:
According to the Snowflake documentation, these two system functions are provided by Snowflake to monitor clustering information within a table. A system function is a type of function that allows executing actions or returning information about the system. A clustering key is a feature that allows organizing data across micro-partitions based on one or more columns in the table. Clustering can improve query performance by reducing the number of files to scan.
* SYSTEM$CLUSTERING_INFORMATION is a system function that returns clustering information, including average clustering depth, for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns a JSON string with the clustering information. The clustering information includes the cluster by keys, the total partition count, the total constant partition count, the average overlaps, and the average depth1.
* SYSTEM$CLUSTERING_DEPTH is a system function that returns the clustering depth for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns an integer value with the clustering depth. The clustering depth is the maximum number of overlapping micro-partitions for any micro-partition in the table. A lower clustering depth indicates a better clustering2.
References:
* SYSTEM$CLUSTERING_INFORMATION | Snowflake Documentation
* SYSTEM$CLUSTERING_DEPTH | Snowflake Documentation
NEW QUESTION # 45
The following table exists in the production database:
A regulatory requirement states that the company must mask the username for events that are older than six months based on the current date when the data is queried.
How can the requirement be met without duplicating the event data and making sure it is applied when creating views using the table or cloning the table?
- A. Use a masking policy on the username column using a entitlement table with valid dates.
- B. Use a masking policy on the username column with event_timestamp as a conditional column.
- C. Use a secure view on the user_events table using a case statement on the username column.
- D. Use a row level policy on the user_events table using a entitlement table with valid dates.
Answer: B
NEW QUESTION # 46
An Architect is integrating an application that needs to read and write data to Snowflake without installing any additional software on the application server.
How can this requirement be met?
- A. Use SnowSQL.
- B. Use the Snowpipe REST API.
- C. Use the Snowflake ODBC driver.
- D. Use the Snowflake SQL REST API.
Answer: D
Explanation:
The Snowflake SQL REST API is a REST API that you can use to access and update data in a Snowflake database. You can use this API to execute standard queries and most DDL and DML statements. This API can be used to develop custom applications and integrations that can read and write data to Snowflake without installing any additional software on the application server. Option A is not correct because SnowSQL is a command-line client that requires installation and configuration on the application server. Option B is not correct because the Snowpipe REST API is used to load data from cloud storage into Snowflake tables, not to read or write data to Snowflake. Option D is not correct because the Snowflake ODBC driver is a software component that enables applications to connect to Snowflake using the ODBC protocol, which also requires installation and configuration on the application server. References: The answer can be verified from Snowflake's official documentation on the Snowflake SQL REST API available on their website. Here are some relevant links:
* Snowflake SQL REST API | Snowflake Documentation
* Introduction to the SQL API | Snowflake Documentation
* Submitting a Request to Execute SQL Statements | Snowflake Documentation
NEW QUESTION # 47
Is it possible for a data provider account with a Snowflake Business Critical edition to share data with an Enterprise edition data consumer account?
- A. If a user in the provider account with a share owning role which also has override share restrictions privilege share_restrictions set to False when adding an Enterprise consumer account, it can import the share.
- B. If a user in the provider account with a share owning role sets share_restrictions to False when adding an Enterprise consumer account, it can import the share.
- C. A Business Critical account cannot be a data sharing provider to an Enterprise consumer. Any consumer accounts must also be Business Critical.
- D. If a user in the provider account with role authority to create or alter share adds an Enterprise account as a consumer, it can import the share.
Answer: A
NEW QUESTION # 48
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) 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 - C. 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 - 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: C
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 # 49
What built-in Snowflake features make use of the change tracking metadata for a table? (Choose two.)
- A. The MERGE command
- B. A STREAM object
- C. The UPSERT command
- D. The CHANGE_DATA_CAPTURE command
- E. The CHANGES clause
Answer: B,E
Explanation:
The built-in Snowflake features that make use of the change tracking metadata for a table are the CHANGES clause and a STREAM object. The CHANGES clause enables querying the change tracking metadata for a table or view within a specified interval of time without having to create a stream with an explicit transactional offset1. A STREAM object records data manipulation language (DML) changes made to tables, including inserts, updates, and deletes, as well as metadata about each change, so that actions can be taken using the changed data. This process is referred to as change data capture (CDC)2. The other options are incorrect because they do not make use of the change tracking metadata for a table. The MERGE command performs insert, update, or delete operations on a target table based on the results of a join with a source table3. The UPSERT command is not a valid Snowflake command. The CHANGE_DATA_CAPTURE command is not a valid Snowflake command. References: CHANGES | Snowflake Documentation, Change Tracking Using Table Streams | Snowflake Documentation, MERGE | Snowflake Documentation
NEW QUESTION # 50
The diagram shows the process flow for Snowpipe auto-ingest with Amazon Simple Notification Service (SNS) with the following steps:
Step 1: Data files are loaded in a stage.
Step 2: An Amazon S3 event notification, published by SNS, informs Snowpipe - by way of Amazon Simple Queue Service (SQS) - that files are ready to load. Snowpipe copies the files into a queue.
Step 3: A Snowflake-provided virtual warehouse loads data from the queued files into the target table based on parameters defined in the specified pipe.
If an AWS Administrator accidentally deletes the SQS subscription to the SNS topic in Step 2, what will happen to the pipe that references the topic to receive event messages from Amazon S3?
- A. The pipe will no longer be able to receive the messages and the user must wait for 24 hours from the time when the SNS topic subscription was deleted. Pipe recreation is not required as the pipe will reuse the same subscription to the existing SNS topic after 24 hours.
- B. The pipe will continue to receive the messages as Snowflake will automatically restore the subscription to the same SNS topic and will recreate the pipe by specifying the same SNS topic name in the pipe definition.
- C. The pipe will continue to receive the messages as Snowflake will automatically restore the subscription by creating a new SNS topic. Snowflake will then recreate the pipe by specifying the new SNS topic name in the pipe definition.
- D. The pipe will no longer be able to receive the messages. To restore the system immediately, the user needs to manually create a new SNS topic with a different name and then recreate the pipe by specifying the new SNS topic name in the pipe definition.
Answer: D
Explanation:
If an AWS Administrator accidentally deletes the SQS subscription to the SNS topic in Step 2, the pipe that references the topic to receive event messages from Amazon S3 will no longer be able to receive the messages. This is because the SQS subscription is the link between the SNS topic and the Snowpipe notification channel. Without the subscription, the SNS topic will not be able to send notifications to the Snowpipe queue, and the pipe will not be triggered to load the new files. To restore the system immediately, the user needs to manually create a new SNS topic with a different name and then recreate the pipe by specifying the new SNS topic name in the pipe definition. This will create a new notification channel and a new SQS subscription for the pipe. Alternatively, the user can also recreate the SQS subscription to the existing SNS topic and then alter the pipe to use the same SNS topic name in the pipe definition. This will also restore the notification channel and the pipe functionality. Reference:
Automating Snowpipe for Amazon S3
Enabling Snowpipe Error Notifications for Amazon SNS
HowTo: Configuration steps for Snowpipe Auto-Ingest with AWS S3 Stages
NEW QUESTION # 51
What are some of the characteristics of result set caches? (Choose three.)
- A. Time Travel queries can be executed against the result set cache.
- B. The retention period can be reset for a maximum of 31 days.
- C. Snowflake persists the data results for 24 hours.
- D. The data stored in the result cache will contribute to storage costs.
- E. The result set cache is not shared between warehouses.
- F. Each time persisted results for a query are used, a 24-hour retention period is reset.
Answer: B,C,F
Explanation:
Comprehensive and Detailed Explanation: According to the SnowPro Advanced: Architect documents and learning resources, some of the characteristics of result set caches are:
Snowflake persists the data results for 24 hours. This means that the result set cache holds the results of every query executed in the past 24 hours, and can be reused if the same query is submitted again and the underlying data has not changed1.
Each time persisted results for a query are used, a 24-hour retention period is reset. This means that the result set cache extends the lifetime of the results every time they are reused, up to a maximum of 31 days from the date and time that the query was first executed1.
The retention period can be reset for a maximum of 31 days. This means that the result set cache will purge the results after 31 days, regardless of whether they are reused or not. After 31 days, the next time the query is submitted, a new result is generated and persisted1.
The other options are incorrect because they are not characteristics of result set caches. Option A is incorrect because Time Travel queries cannot be executed against the result set cache. Time Travel queries use the AS OF clause to access historical data that is stored in the storage layer, not the result set cache2. Option D is incorrect because the data stored in the result set cache does not contribute to storage costs. The result set cache is maintained by the service layer, and does not incur any additional charges1. Option F is incorrect because the result set cache is shared between warehouses. The result set cache is available across virtual warehouses, so query results returned to one user are available to any other user on the system who executes the same query, provided the underlying data has not changed1. Reference: Using Persisted Query Results | Snowflake Documentation, Time Travel | Snowflake Documentation
NEW QUESTION # 52
Which system functions does Snowflake provide to monitor clustering information within a table (Choose two.)
- A. SYSTEM$CLUSTERING_KEYS
- B. SYSTEM$CLUSTERING_INFORMATION
- C. SYSTEM$CLUSTERING_PERCENT
- D. SYSTEM$CLUSTERING_DEPTH
- E. SYSTEM$CLUSTERING_USAGE
Answer: B,D
Explanation:
According to the Snowflake documentation, these two system functions are provided by Snowflake to monitor clustering information within a table. A system function is a type of function that allows executing actions or returning information about the system. A clustering key is a feature that allows organizing data across micro-partitions based on one or more columns in the table. Clustering can improve query performance by reducing the number of files to scan.
SYSTEM$CLUSTERING_INFORMATION is a system function that returns clustering information, including average clustering depth, for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns a JSON string with the clustering information. The clustering information includes the cluster by keys, the total partition count, the total constant partition count, the average overlaps, and the average depth1.
SYSTEM$CLUSTERING_DEPTH is a system function that returns the clustering depth for a table based on one or more columns in the table. The function takes a table name and an optional column name or expression as arguments, and returns an integer value with the clustering depth. The clustering depth is the maximum number of overlapping micro-partitions for any micro-partition in the table. A lower clustering depth indicates a better clustering2.
Reference:
SYSTEM$CLUSTERING_INFORMATION | Snowflake Documentation
SYSTEM$CLUSTERING_DEPTH | Snowflake Documentation
NEW QUESTION # 53
What are purposes for creating a storage integration? (Choose three.)
- A. Avoid supplying credentials when creating a stage or when loading or unloading data.
- B. Control access to Snowflake data using a master encryption key that is maintained in the cloud provider's key management service.
- C. Store a generated identity and access management (IAM) entity for an external cloud provider regardless of the cloud provider that hosts the Snowflake account.
- D. Manage credentials from multiple cloud providers in one single Snowflake object.
- E. Support multiple external stages using one single Snowflake object.
- F. Create private VPC endpoints that allow direct, secure connectivity between VPCs without traversing the public internet.
Answer: A,C,E
Explanation:
The purpose of creating a storage integration in Snowflake includes:B. Store a generated identity and access management (IAM) entity for an external cloud provider - This helps in managing authentication and authorization with external cloud storage without embedding credentials in Snowflake. It supports various cloud providers like AWS, Azure, or GCP, ensuring that the identity management is streamlined across platforms.C. Support multiple external stages using one single Snowflake object - Storage integrations allow you to set up access configurations that can be reused across multiple external stages, simplifying the management of external data integrations.D. Avoid supplying credentials when creating a stage or when loading or unloading data - By using a storage integration, Snowflake can interact with external storage without the need to continuously manage or expose sensitive credentials, enhancing security and ease of operations.References: Snowflake documentation on storage integrations, found within the SnowPro Advanced: Architect course materials.
NEW QUESTION # 54
......
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