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NEW QUESTION # 29
A Snowflake Architect is designing a multiple-account design strategy.
This strategy will be MOST cost-effective with which scenarios? (Select TWO).
- A. The company must use a specific network policy for certain users to allow and block given IP addresses.
- B. The company wants to clone a production database that resides on AWS to a development database that resides on Azure.
- C. The company needs to support different role-based access control features for the development, test, and production environments.
- D. The company security policy mandates the use of different Active Directory instances for the development, test, and production environments.
- E. The company needs to share data between two databases, where one must support Payment Card Industry Data Security Standard (PCI DSS) compliance but the other one does not.
Answer: C,E
Explanation:
A multiple-account design strategy is a way of organizing Snowflake accounts into logical groups based on different criteria, such as cloud provider, region, environment, or business unit. A multiple-account design strategy can help achieve various goals, such as cost optimization, performance isolation, security compliance, and data sharing1. In this question, the scenarios that would be most cost-effective with a multiple-account design strategy are:
The company wants to clone a production database that resides on AWS to a development database that resides on Azure. This scenario would benefit from a multiple-account design strategy because it would allow the company to leverage the cross-cloud replication feature of Snowflake, which enables replicating databases across different cloud platforms and regions. This feature can help reduce the data transfer costs and latency, as well as provide high availability and disaster recovery2.
The company security policy mandates the use of different Active Directory instances for the development, test, and production environments. This scenario would benefit from a multiple-account design strategy because it would allow the company to use different federated authentication methods for each environment, and integrate them with different Active Directory instances. This can help improve the security and governance of the access to the Snowflake accounts, as well as simplify the user management and provisioning3.
The other scenarios would not be most cost-effective with a multiple-account design strategy, because:
The company needs to share data between two databases, where one must support Payment Card Industry Data Security Standard (PCI DSS) compliance but the other one does not. This scenario can be handled within a single Snowflake account, by using secure views and secure UDFs to mask or filter the sensitive data, and applying the appropriate roles and privileges to the users who access the data. This can help achieve the PCI DSS compliance without incurring the additional costs of managing multiple accounts4.
The company needs to support different role-based access control features for the development, test, and production environments. This scenario can also be handled within a single Snowflake account, by using the native role-based access control (RBAC) features of Snowflake, such as roles, grants, and privileges, to define different access levels and permissions for each environment. This can help ensure the security and integrity of the data and the objects, as well as the separation of duties and responsibilities among the users.
The company must use a specific network policy for certain users to allow and block given IP addresses.
This scenario can also be handled within a single Snowflake account, by using the network policy feature of Snowflake, which enables creating and applying network policies to restrict the IP addresses that can access the Snowflake account. This can help prevent unauthorized access and protect the data from malicious attacks.
References:
Designing Your Snowflake Topology
Cross-Cloud Replication
Configuring Federated Authentication and SSO
Using Secure Views and Secure UDFs to Comply with PCI DSS
[Understanding Access Control in Snowflake]
[Network Policies]
NEW QUESTION # 30
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. There needs to be fewer objects per tenant.
- B. Tenant data shape may be unique per tenant.
- C. Compute costs must be optimized.
- D. Storage costs must be optimized.
- E. Security and Role-Based Access Control (RBAC) policies must be simple to configure.
Answer: B,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 # 31
What step will improve the performance of queries executed against an external table?
- A. Convert the source files' character encoding to UTF-8.
- B. Use an internal stage instead of an external stage to store the source files.
- C. Partition the external table.
- D. Shorten the names of the source files.
Answer: C
Explanation:
Partitioning an external table is a technique that improves the performance of queries executed against the table by reducing the amount of data scanned. Partitioning an external table involves creating one or more partition columns that define how the table is logically divided into subsets of data based on the values in those columns. The partition columns can be derived from the file metadata (such as file name, path, size, or modification time) or from the file content (such as a column value or a JSON attribute). Partitioning an external table allows the query optimizer to prune the files that do not match the query predicates, thus avoiding unnecessary data scanning and processing2 The other options are not effective steps for improving the performance of queries executed against an external table:
Shorten the names of the source files. This option does not have any impact on the query performance, as the file names are not used for query processing. The file names are only used for creating the external table and displaying the query results3 Convert the source files' character encoding to UTF-8. This option does not affect the query performance, as Snowflake supports various character encodings for external table files, such as UTF-8, UTF-16, UTF-32, ISO-8859-1, and Windows-1252. Snowflake automatically detects the character encoding of the files and converts them to UTF-8 internally for query processing4 Use an internal stage instead of an external stage to store the source files. This option is not applicable, as external tables can only reference files stored in external stages, such as Amazon S3, Google Cloud Storage, or Azure Blob Storage. Internal stages are used for loading data into internal tables, not external tables5 References:
1: SnowPro Advanced: Architect | Study Guide
2: Snowflake Documentation | Partitioning External Tables
3: Snowflake Documentation | Creating External Tables
4: Snowflake Documentation | Supported File Formats and Compression for Staged Data Files
5: Snowflake Documentation | Overview of Stages
: SnowPro Advanced: Architect | Study Guide
: Partitioning External Tables
: Creating External Tables
: Supported File Formats and Compression for Staged Data Files
: Overview of Stages
NEW QUESTION # 32
An Architect needs to allow a user to create a database from an inbound share.
To meet this requirement, the user's role must have which privileges? (Choose two.)
- A. IMPORT PRIVILEGES;
- B. IMPORT SHARE;
- C. CREATE SHARE;
- D. IMPORT DATABASE;
- E. CREATE DATABASE;
Answer: D,E
Explanation:
According to the Snowflake documentation, to create a database from an inbound share, the user's role must have the following privileges:
The CREATE DATABASE privilege on the current account. This privilege allows the user to create a new database in the account1.
The IMPORT DATABASE privilege on the share. This privilege allows the user to import a database from the share into the account2. The other privileges listed are not relevant for this requirement. The IMPORT SHARE privilege is used to import a share into the account, not a database3. The IMPORT PRIVILEGES privilege is used to import the privileges granted on the shared objects, not the objects themselves2. The CREATE SHARE privilege is used to create a share to provide data to other accounts, not to consume data from other accounts4.
References:
CREATE DATABASE | Snowflake Documentation
Importing Data from a Share | Snowflake Documentation
Importing a Share | Snowflake Documentation
CREATE SHARE | Snowflake Documentation
NEW QUESTION # 33
An Architect needs to meet a company requirement to ingest files from the company's AWS storage accounts into the company's Snowflake Google Cloud Platform (GCP) account. How can the ingestion of these files into the company's Snowflake account be initiated? (Select TWO).
- A. Configure the client application to issue a COPY INTO <TABLE> command to Snowflake when new files have arrived in Amazon S3 Glacier storage.
- B. Configure AWS Simple Notification Service (SNS) to notify Snowpipe when new files have arrived in Amazon S3 storage.
- C. Configure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage.
- D. Create an AWS Lambda function to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage.
- E. Configure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 Glacier storage.
Answer: C,D
Explanation:
Snowpipe is a feature that enables continuous, near-real-time data ingestion from external sources into Snowflake tables. Snowpipe can ingest files from Amazon S3, GoogleCloud Storage, or Azure Blob Storage into Snowflake tables on any cloud platform. Snowpipe can be triggered in two ways: by using the Snowpipe REST API or by using cloud notifications2 To ingest files from the company's AWS storage accounts into the company's Snowflake GCP account, the Architect can use either of these methods:
Configure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage. This method requires the client application to monitor the S3 buckets for new files and send a request to the Snowpipe REST API with the list of files to ingest. The client application must also handle authentication, error handling, and retry logic3 Create an AWS Lambda function to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 storage. This method leverages the AWS Lambda service to execute a function that calls the Snowpipe REST API whenever an S3 event notification is received. The AWS Lambda function must be configured with the appropriate permissions, triggers, and code to invoke the Snowpipe REST API4 The other options are not valid methods for triggering Snowpipe:
Configure the client application to call the Snowpipe REST endpoint when new files have arrived in Amazon S3 Glacier storage. This option is not feasible because Snowpipe does not support ingesting files from Amazon S3 Glacier storage, which is a long-term archival storage service. Snowpipe only supports ingesting files from Amazon S3 standard storage classes5 Configure AWS Simple Notification Service (SNS) to notify Snowpipe when new files have arrived in Amazon S3 storage. This option is not applicable because Snowpipe does not support cloud notifications from AWS SNS. Snowpipe only supports cloud notifications from AWS SQS, Google Cloud Pub/Sub, or Azure Event Grid6 Configure the client application to issue a COPY INTO <TABLE> command to Snowflake when new files have arrived in Amazon S3 Glacier storage. This option is not relevant because it does not use Snowpipe, but rather the standard COPY command, which is a batch loading method. Moreover, the COPY command also does not support ingesting files from Amazon S3 Glacier storage7 References:
1: SnowPro Advanced: Architect | Study Guide 8
2: Snowflake Documentation | Snowpipe Overview 9
3: Snowflake Documentation | Using the Snowpipe REST API 10
4: Snowflake Documentation | Loading Data Using Snowpipe and AWS Lambda 11
5: Snowflake Documentation | Supported File Formats and Compression for Staged Data Files 12
6: Snowflake Documentation | Using Cloud Notifications to Trigger Snowpipe 13
7: Snowflake Documentation | Loading Data Using COPY into a Table
: SnowPro Advanced: Architect | Study Guide
: Snowpipe Overview
: Using the Snowpipe REST API
: Loading Data Using Snowpipe and AWS Lambda
: Supported File Formats and Compression for Staged Data Files
: Using Cloud Notifications to Trigger Snowpipe
: Loading Data Using COPY into a Table
NEW QUESTION # 34
Consider the following scenario where a masking policy is applied on the CREDICARDND column of the CREDITCARDINFO table. The masking policy definition Is as follows:
Sample data for the CREDITCARDINFO table is as follows:
NAME EXPIRYDATE CREDITCARDNO
JOHN DOE 2022-07-23 4321 5678 9012 1234
if the Snowflake system rotes have not been granted any additional roles, what will be the result?
- A. The owner of the table will see the CREDICARDND column data in clear text.
- B. Anyone with the Pl_ANALYTICS role will see the CREDICARDND column as*** 'MASKED* **'.
- C. Anyone with the Pl_ANALYTICS role will see the last 4 characters of the CREDICARDND column data in dear text.
- D. The sysadmin can see the CREDICARDND column data in clear text.
Answer: B
Explanation:
The masking policy defined in the image indicates that if a user has the PI_ANALYTICS role, they will be able to see the last 4 characters of the CREDITCARDNO column data in clear text. Otherwise, they will see 'MASKED'. Since Snowflake system roles have not been granted any additional roles, they won't have the PI_ANALYTICS role and therefore cannot view the last 4 characters of credit card numbers.
To apply a masking policy on a column in Snowflake, you need to use the ALTER TABLE ... ALTER COLUMN command or the ALTER VIEW command and specify the policy name. For example, to apply the creditcardno_mask policy on the CREDITCARDNO column of the CREDITCARDINFO table, you can use the following command:
ALTER TABLE CREDITCARDINFO ALTER COLUMN CREDITCARDNO SET MASKING POLICY creditcardno_mask; For more information on how to create and use masking policies in Snowflake, you can refer to the following resources:
CREATE MASKING POLICY: This document explains the syntax and usage of the CREATE MASKING POLICY command, which allows you to create a new masking policy or replace an existing one.
Using Dynamic Data Masking: This guide provides instructions on how to configure and use dynamic data masking in Snowflake, which is a feature that allows you to mask sensitive data based on the execution context of the user.
ALTER MASKING POLICY: This document explains the syntax and usage of the ALTER MASKING POLICY command, which allows you to modify the properties of an existing masking policy.
References: 1: https://docs.snowflake.com/en/sql-reference/sql/create-masking-policy 2:
https://docs.snowflake.com/en/user-guide/security-column-ddm-use 3:
https://docs.snowflake.com/en/sql-reference/sql/alter-masking-policy
NEW QUESTION # 35
A company is designing high availability and disaster recovery plans and needs to maximize redundancy and minimize recovery time objectives for their critical application processes. Cost is not a concern as long as the solution is the best available. The plan so far consists of the following steps:
1. Deployment of Snowflake accounts on two different cloud providers.
2. Selection of cloud provider regions that are geographically far apart.
3. The Snowflake deployment will replicate the databases and account data between both cloud provider accounts.
4. Implementation of Snowflake client redirect.
What is the MOST cost-effective way to provide the HIGHEST uptime and LEAST application disruption if there is a service event?
- A. Connect the applications using the <organization_name>-<accountLocator> URL. Use the Enterprise Snowflake edition.
- B. Connect the applications using the <organization_name>-<connection_name> URL. Use the Virtual Private Snowflake (VPS) edition.
- C. Connect the applications using the <organization_name>-<connection_name> URL. Use the Business Critical Snowflake edition.
- D. Connect the applications using the <organization_name>-<accountLocator> URL. Use the Business Critical Snowflake edition.
Answer: D
Explanation:
To provide the highest uptime and least application disruption in case of a service event, the best option is to use the Business Critical Snowflake edition and connect the applications using the
<organization_name>-<accountLocator> URL. The Business CriticalSnowflake edition offers the highest level of security, performance, and availability for Snowflake accounts. It includes features such as customer-managed encryption keys, HIPAA compliance, and 4-hour RPO and RTO SLAs. It also supports account replication and failover across regions and cloud platforms, which enables business continuity and disaster recovery. By using the <organization_name>-<accountLocator> URL, the applications can leverage the Snowflake Client Redirect feature, which automatically redirects the client connections to the secondary account in case of a failover. This way, the applications can seamlessly switch to the backup account without any manual intervention or configuration changes. The other options are less cost-effective or less reliable because they either use a lower edition of Snowflake, which does not support account replication and failover, or they use the <organization_name>-<connection_name> URL, which does not support client redirect and requires manual updates to the connection string in case of a failover. References:
[Snowflake Editions] 1
[Replication and Failover/Failback] 2
[Client Redirect] 3
[Snowflake Account Identifiers] 4
NEW QUESTION # 36
An Architect entered the following commands in sequence:
USER1 cannot find the table.
Which of the following commands does the Architect need to run for USER1 to find the tables using the Principle of Least Privilege? (Choose two.)
- A. GRANT ALL PRIVILEGES ON DATABASE SANDBOX TO ROLE INTERN;
- B. GRANT USAGE ON SCHEMA SANDBOX.PUBLIC TO ROLE INTERN;
- C. GRANT USAGE ON DATABASE SANDBOX TO ROLE INTERN;
- D. GRANT OWNERSHIP ON DATABASE SANDBOX TO USER INTERN;
- E. GRANT ROLE PUBLIC TO ROLE INTERN;
Answer: B,C
Explanation:
According to the Principle of Least Privilege, the Architect should grant the minimum privileges necessary for the USER1 to find the tables in the SANDBOX database.
The USER1 needs to have USAGE privilege on the SANDBOX database and the SANDBOX.PUBLIC schema to be able to access the tables in the PUBLIC schema. Therefore, the commands B and C are the correct ones to run.
The command A is not correct because the PUBLIC role is automatically granted to every user and role in the account, and it does not have any privileges on the SANDBOX database by default.
The command D is not correct because it would transfer the ownership of the SANDBOX database from the Architect to the USER1, which is not necessary and violates the Principle of Least Privilege.
The command E is not correct because it would grant all the possible privileges on the SANDBOX database to the USER1, which is also not necessary and violates the Principle of Least Privilege.
References: : Snowflake - Principle of Least Privilege : Snowflake - Access Control Privileges : Snowflake - Public Role : Snowflake - Ownership and Grants
NEW QUESTION # 37
An Architect has a design where files arrive every 10 minutes and are loaded into a primary database table using Snowpipe. A secondary database is refreshed every hour with the latest data from the primary database.
Based on this scenario, what Time Travel query options are available on the secondary database?
- A. A query using Time Travel in the secondary database is available for every hourly table version within and outside the retention window.
- B. Using Time Travel, secondary database users can query every iterative version within each hour (the individual Snowpipe loads) in the retention window.
- C. Using Time Travel, secondary database users can query every iterative version within each hour (the individual Snowpipe loads) and outside the retention window.
- D. A query using Time Travel in the secondary database is available for every hourly table version within the retention window.
Answer: D
Explanation:
Snowflake's Time Travel feature allows users to query historical data within a defined retention period. In the given scenario, since the secondary database is refreshed every hour, Time Travel can be used to query each hourly version of the table as long as it falls within the retention window. This does not include individual Snowpipe loads within each hour unless they coincide with the hourly refresh.
References: The answer is verified using Snowflake's official documentation, which provides detailed information on Time Travel and its usage within the retention period123.
NEW QUESTION # 38
An Architect needs to allow a user to create a database from an inbound share.
To meet this requirement, the user's role must have which privileges? (Choose two.)
- A. IMPORT PRIVILEGES;
- B. IMPORT SHARE;
- C. CREATE SHARE;
- D. IMPORT DATABASE;
- E. CREATE DATABASE;
Answer: D,E
Explanation:
According to the Snowflake documentation, to create a database from an inbound share, the user's role must have the following privileges:
* The CREATE DATABASE privilege on the current account. This privilege allows the user to create a new database in the account1.
* The IMPORT DATABASE privilege on the share. This privilege allows the user to import a database from the share into the account2. The other privileges listed are not relevant for this requirement. The IMPORT SHARE privilege is used to import a share into the account, not a database3. The IMPORT PRIVILEGES privilege is used to import the privileges granted on the shared objects, not the objects
* themselves2. The CREATE SHARE privilege is used to create a share to provide data to other accounts, not to consume data from other accounts4.
References:
* CREATE DATABASE | Snowflake Documentation
* Importing Data from a Share | Snowflake Documentation
* Importing a Share | Snowflake Documentation
* CREATE SHARE | Snowflake Documentation
NEW QUESTION # 39
An Architect is troubleshooting a query with poor performance using the QUERY_HIST0RY function. The Architect observes that the COMPILATIONJHME is greater than the EXECUTIONJTIME.
What is the reason for this?
- A. The query is processing a very large dataset.
- B. The query is reading from remote storage.
- C. The query has overly complex logic.
- D. The query is queued for execution.
Answer: C
Explanation:
Compilation time is the time it takes for the optimizer to create an optimal query plan for the efficient execution of the query. It also involves some pruning of partition files, making the query execution efficient2 If the compilation time is greater than the execution time, it means that the optimizer spent more time analyzing the query than actually running it. This could indicate that the query has overly complex logic, such as multiple joins, subqueries, aggregations, or expressions. The complexity of the query could also affect the size and quality of the query plan, which could impact the performance of the query3 To reduce the compilation time, the Architect can try to simplify the query logic, use views or common table expressions (CTEs) to break down the query into smaller parts, or use hints to guide the optimizer. The Architect can also use the EXPLAIN command to examine the query plan and identify potential bottlenecks or inefficiencies4 References:
1: SnowPro Advanced: Architect | Study Guide 5
2: Snowflake Documentation | Query Profile Overview 6
3: Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time 7
4: Snowflake Documentation | Optimizing Query Performance 8
: SnowPro Advanced: Architect | Study Guide
: Query Profile Overview
: Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time
: Optimizing Query Performance
NEW QUESTION # 40
A Data Engineer is designing a near real-time ingestion pipeline for a retail company to ingest event logs into Snowflake to derive insights. A Snowflake Architect is asked to define security best practices to configure access control privileges for the data load for auto-ingest to Snowpipe.
What are the MINIMUM object privileges required for the Snowpipe user to execute Snowpipe?
- A. CREATE on the named pipe, USAGE and READ on the named stage, USAGE on the target database and schema, and INSERT end SELECT on the target table
- B. OWNERSHIP on the named pipe, USAGE and READ on the named stage, USAGE on the target database and schema, and INSERT end SELECT on the target table
- C. OWNERSHIP on the named pipe, USAGE on the named stage, target database, and schema, and INSERT and SELECT on the target table
- D. USAGE on the named pipe, named stage, target database, and schema, and INSERT and SELECT on the target table
Answer: B
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the minimum object privileges required for the Snowpipe user to execute Snowpipe are:
OWNERSHIP on the named pipe. This privilege allows the Snowpipe user to create, modify, and drop the pipe object that defines the COPY statement for loading data from the stage to the table1.
USAGE and READ on the named stage. These privileges allow the Snowpipe user to access and read the data files from the stage that are loaded by Snowpipe2.
USAGE on the target database and schema. These privileges allow the Snowpipe user to access the database and schema that contain the target table3.
INSERT and SELECT on the target table. These privileges allow the Snowpipe user to insert data into the table and select data from the table4.
The other options are incorrect because they do not specify the minimum object privileges required for the Snowpipe user to execute Snowpipe. Option A is incorrect because it does not include the READ privilege on the named stage, which is required for the Snowpipe user to read the data files from the stage. Option C is incorrect because it does not include the OWNERSHIP privilege on the named pipe, which is required for the Snowpipe user to create, modify, and drop the pipe object. Option D is incorrect because it does not include the OWNERSHIP privilege on the named pipe or the READ privilege on the named stage, which are both required for the Snowpipe user to execute Snowpipe. References: CREATE PIPE | Snowflake Documentation, CREATE STAGE | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation, CREATE TABLE | Snowflake Documentation
NEW QUESTION # 41
An Architect has been asked to clone schema STAGING as it looked one week ago, Tuesday June 1st at 8:00 AM, to recover some objects.
The STAGING schema has 50 days of retention.
The Architect runs the following statement:
CREATE SCHEMA STAGING_CLONE CLONE STAGING at (timestamp => '2021-06-01 08:00:00'); The Architect receives the following error: Time travel data is not available for schema STAGING. The requested time is either beyond the allowed time travel period or before the object creation time.
The Architect then checks the schema history and sees the following:
CREATED_ON|NAME|DROPPED_ON
2021-06-02 23:00:00 | STAGING | NULL
2021-05-01 10:00:00 | STAGING | 2021-06-02 23:00:00
How can cloning the STAGING schema be achieved?
- A. Rename the STAGING schema and perform an UNDROP to retrieve the previous STAGING schema version, then run the CLONE statement.
- B. Cloning cannot be accomplished because the STAGING schema version was not active during the proposed Time Travel time period.
- C. Modify the statement: CREATE SCHEMA STAGING_CLONE CLONE STAGING at (timestamp =>
'2021-05-01 10:00:00'); - D. Undrop the STAGING schema and then rerun the CLONE statement.
Answer: A
Explanation:
The error message indicates that the schema STAGING does not have time travel data available for the requested timestamp, because the current version of the schema was created on 2021-06-02 23:00:00, which is after the timestamp of 2021-06-01 08:00:00. Therefore, the CLONE statement cannot access the historical data of the schema at that point in time.
Option A is incorrect, because undropping the STAGING schema will not restore the previous version of the schema that was active on 2021-06-01 08:00:00. Instead, it will create a new version of the schema with the same name and no data or objects.
Option B is incorrect, because modifying the timestamp to 2021-05-01 10:00:00 will not clone the schema as it looked one week ago, but as it looked when it was first created. This may not reflect the desired state of the schema and its objects.
Option C is correct, because renaming the STAGING schema and performing an UNDROP to retrieve the previous STAGING schema version will restore the schema that was dropped on 2021-06-02
23:00:00. This schema has time travel data available for the requested timestamp of 2021-06-01
08:00:00, and can be cloned using the CLONE statement.
Option D is incorrect, because cloning can be accomplished by using the UNDROP command to access the previous version of the schema that was active during the proposed time travel period.
References: : Cloning Considerations : Understanding & Using Time Travel : CREATE <object> ... CLONE
NEW QUESTION # 42
An Architect is designing a pipeline to stream event data into Snowflake using the Snowflake Kafka connector. The Architect's highest priority is to configure the connector to stream data in the MOST cost-effective manner.
Which of the following is recommended for optimizing the cost associated with the Snowflake Kafka connector?
- A. Utilize a lower Buffer.size.bytes in the connector configuration.
- B. Utilize a lower Buffer.count.records in the connector configuration.
- C. Utilize a higher Buffer.flush.time in the connector configuration.
- D. Utilize a higher Buffer.size.bytes in the connector configuration.
Answer: C
Explanation:
The minimum value supported for the buffer.flush.time property is 1 (in seconds). For higher average data flow rates, we suggest that you decrease the default value for improved latency. If cost is a greater concern than latency, you could increase the buffer flush time. Be careful to flush the Kafka memory buffer before it becomes full to avoid out of memory exceptions.
https://docs.snowflake.com/en/user-guide/data-load-snowpipe-streaming-kafka
NEW QUESTION # 43
A Snowflake Architect is designing an application and tenancy strategy for an organization where strong legal isolation rules as well as multi-tenancy are requirements.
Which approach will meet these requirements if Role-Based Access Policies (RBAC) is a viable option for isolating tenants?
- A. Create an object for each tenant strategy if row level security is viable for isolating tenants.
- B. Create a multi-tenant table strategy if row level security is not viable for isolating tenants.
- C. Create an object for each tenant strategy if row level security is not viable for isolating tenants.
- D. Create accounts for each tenant in the Snowflake organization.
Answer: D
Explanation:
In a scenario where strong legal isolation is required alongside the need for multi-tenancy, the most effective approach is to create separate accounts for each tenant within the Snowflake organization. This approach ensures complete isolation of data, resources, and management, adhering to strict legal and compliance requirements. Role-Based Access Control (RBAC) further enhances security by allowing granular control over who can access what resources within each account. This solution leverages Snowflake's capabilities for managing multiple accounts under a single organization umbrella, ensuring that each tenant's data and operations are isolated from others.References: Snowflake documentation on multi-tenancy and account management, part of the SnowPro Advanced: Architect learning path.
NEW QUESTION # 44
Which steps are recommended best practices for prioritizing cluster keys in Snowflake? (Choose two.)
- A. Choose lower cardinality columns to support clustering keys and cost effectiveness.
- B. Choose cluster columns that are most actively used in selective filters.
- C. Choose TIMESTAMP columns with nanoseconds for the highest number of unique rows.
- D. Choose cluster columns that are actively used in the GROUP BY clauses.
- E. Choose columns that are frequently used in join predicates.
Answer: B,E
Explanation:
According to the Snowflake documentation, the best practices for choosing clustering keys are:
Choose columns that are frequently used in join predicates. This can improve the join performance by reducing the number of micro-partitions that need to be scanned and joined.
Choose columns that are most actively used in selective filters. This can improve the scan efficiency by skipping micro-partitions that do not match the filter predicates.
Avoid using low cardinality columns, such as gender or country, as clustering keys. This can result in poor clustering and high maintenance costs.
Avoid using TIMESTAMP columns with nanoseconds, as they tend to have very high cardinality and low correlation with other columns. This can also result in poor clustering and high maintenance costs.
Avoid using columns with duplicate values or NULLs, as they can cause skew in the clustering and reduce the benefits of pruning.
Cluster on multiple columns if the queries use multiple filters or join predicates. This can increase the chances of pruning more micro-partitions and improve the compression ratio.
Clustering is not always useful, especially for small or medium-sized tables, or tables that are not frequently queried or updated. Clustering can incur additional costs for initially clustering the data and maintaining the clustering over time.
References:
Clustering Keys & Clustered Tables | Snowflake Documentation
[Considerations for Choosing Clustering for a Table | Snowflake Documentation]
NEW QUESTION # 45
How is the change of local time due to daylight savings time handled in Snowflake tasks? (Choose two.)
- A. A task scheduled in a UTC-based schedule will have no issues with the time changes.
- B. A task schedule will follow only the specified time and will fail to handle lost or duplicated hours.
- C. Task schedules can be designed to follow specified or local time zones to accommodate the time changes.
- D. A frequent task execution schedule like minutes may not cause a problem, but will affect the task history.
- E. A task will move to a suspended state during the daylight savings time change.
Answer: A,C
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 # 46
How do Snowflake databases that are created from shares differ from standard databases that are not created from shares? (Choose three.)
- A. Shared databases can also be created as transient databases.
- B. Shared databases are not supported by Time Travel.
- C. Shared databases must be refreshed in order for new data to be visible.
- D. Shared databases are read-only.
- E. Shared databases will have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share.
- F. Shared databases cannot be cloned.
Answer: B,D,F
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares are:
Shared databases are read-only. This means that the data consumers who access the shared databases cannot modify or delete the data or the objects in the databases. The data providers who share the databases have full control over the data and the objects, and can grant or revoke privileges on them1.
Shared databases cannot be cloned. This means that the data consumers who access the shared databases cannot create a copy of the databases or the objects in the databases. The data providers who share the databases can clone the databases or the objects, but the clones are not automatically shared2.
Shared databases are not supported by Time Travel. This means that the data consumers who access the shared databases cannot use the AS OF clause to query historical data or restore deleted data. The data providers who share the databases can use Time Travel on the databases or the objects, but the historical data is not visible to the data consumers3.
The other options are incorrect because they are not ways that Snowflake databases that are created from shares differ from standard databases that are not created from shares. Option B is incorrect because shared databases do not need to be refreshed in order for new data to be visible. The data consumers who access the shared databases can see the latest data as soon as the data providers update the data1. Option E is incorrect because shared databases will not have the PUBLIC or INFORMATION_SCHEMA schemas without explicitly granting these schemas to the share. The data consumers who access the shared databases can only see the objects that the data providers grant to the share, and the PUBLIC and INFORMATION_SCHEMA schemas are not granted by default4. Option F is incorrect because shared databases cannot be created as transient databases. Transient databases are databases that do not support Time Travel or Fail-safe, and can be dropped without affecting the retention period of the data. Shared databases are always created as permanent databases, regardless of the type of the source database5. References: Introduction to Secure Data Sharing | Snowflake Documentation, Cloning Objects | Snowflake Documentation, Time Travel | Snowflake Documentation, Working with Shares | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation
NEW QUESTION # 47
You are a snowflake architect in an organization. The business team came to to deploy an use case which requires you to load some data which they can visualize through tableau. Everyday new data comes in and the old data is no longer required.
What type of table you will use in this case to optimize cost
- A. TRANSIENT
- B. TEMPORARY
- C. PERMANENT
Answer: A
Explanation:
A transient table is a type of table in Snowflake that does not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. Transient tables are suitable for temporary or intermediate data that can be easily reproduced or replicated1.
A temporary table is a type of table in Snowflake that is automatically dropped when the session ends or the current user logs out. Temporary tables do not incur any storage costs, but they are not visible to other users or sessions2.
A permanent table is a type of table in Snowflake that has a Fail-safe period and a Time Travel retention period of up to 90 days. Permanent tables are suitable for persistent and durable data that needs to be protected from accidental or malicious deletion3.
In this case, the use case requires loading some data that can be visualized through Tableau. The data is updated every day and the old data is no longer required. Therefore, the best type of table to use in this case to optimize cost is a transient table, because it does not incur any Fail-safe costs and it can have a short Time Travel retention period of 0 or 1 day. This way, the data can be loaded and queried by Tableau, and then deleted or overwritten without incurring any unnecessary storage costs.
References: : Transient Tables : Temporary Tables : Understanding & Using Time Travel
NEW QUESTION # 48
What are characteristics of Dynamic Data Masking? (Select TWO).
- A. A masking policy can be applied to a column with the GEOGRAPHY data type.
- B. A single masking policy can be applied to columns in different tables.
- C. The role that creates the masking policy will always see unmasked data In query results
- D. A masking policy can be applied to the value column of an external table.
- E. A masking policy that Is currently set on a table can be dropped.
Answer: B,E
Explanation:
Dynamic Data Masking is a feature that allows masking sensitive data in query results based on the role of the user who executes the query. A masking policy is a user-defined function that specifies the masking logic and can be applied to one or more columns in one or more tables. A masking policy that is currently set on a table can be dropped using the ALTER TABLE command. A single masking policy can be applied to columns in different tables usingthe ALTER TABLE command with the SET MASKING POLICY clause. The other options are either incorrect or not supported by Snowflake. A masking policy cannot be applied to the value column of an external table, as external tables do not support column-level security. The role that creates the masking policy will not always see unmasked data in query results, as the masking policy can be applied to the owner role as well. A masking policy cannot be applied to a column with the GEOGRAPHY data type, as Snowflake only supports masking policies for scalar data types. References: Snowflake Documentation:
Dynamic Data Masking, Snowflake Documentation: ALTER TABLE
NEW QUESTION # 49
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