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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q93-Q98):

NEW QUESTION # 93
What considerations need to be taken when using database cloning as a tool for data lifecycle management in a development environment? (Select TWO).

A. Any pipes in the source referring to external stages are not cloned.
B. Any pipes in the source are not cloned.
C. Any pipes in the source referring to internal stages are not cloned.
D. The clone inherits all granted privileges of all child objects in the source object, including the database.
E. The clone inherits all granted privileges of all child objects in the source object, excluding the database.

Answer: B,D

Explanation:
Database cloning is a feature of Snowflake that allows creating a copy of a database, schema, table, or view without consuming any additional storage space. Database cloning can be used as a tool for data lifecycle management in a development environment, where developers and testers can work on isolated copies of production data without affecting the original data or each other1.
However, there are some considerations that need to be taken when using database cloning in a development environment, such as:
Any pipes in the source are not cloned. Pipes are objects that load data from a stage into a table continuously. Pipes are not cloned because they are associated with a specific stage and table, and cloning them would create duplicate data loading and potential conflicts2.
The clone inherits all granted privileges of all child objects in the source object, including the database. Privileges are the permissions that control the access and actions that can be performed on an object. When a database is cloned, the clone inherits all the privileges that were granted on the source database and its child objects, such as schemas, tables, and views. This means that the same roles that can access and modify the source database can also access and modify the clone, unless the privileges are explicitly revoked or modified3.
The other options are not correct because:
B) Any pipes in the source referring to internal stages are not cloned. This is a subset of option A, which states that any pipes in the source are not cloned, regardless of the type of stage they refer to.
C) Any pipes in the source referring to external stages are not cloned. This is also a subset of option A, which states that any pipes in the source are not cloned, regardless of the type of stage they refer to.
E) The clone inherits all granted privileges of all child objects in the source object, excluding the database. This is incorrect, as the clone inherits all granted privileges of the source object, including the database.
Reference:
1: Database Cloning | Snowflake Documentation
2: Pipes | Snowflake Documentation
3: Access Control Privileges | Snowflake Documentation

NEW QUESTION # 94
Consider the following COPY command which is loading data with CSV format into a Snowflake table from an internal stage through a data transformation query.

This command results in the following error:
SQL compilation error: invalid parameter 'validation_mode'
Assuming the syntax is correct, what is the cause of this error?

A. The VALIDATION_MODE parameter does not support COPY statements with CSV file formats.
B. The VALIDATION_MODE parameter supports COPY statements that load data from external stages only.
C. The VALIDATION_MODE parameter does not support COPY statements that transform data during a load.
D. The value return_all_errors of the option VALIDATION_MODE is causing a compilation error.

Answer: C

Explanation:
Explanation
* The VALIDATION_MODE parameter is used to specify the behavior of the COPY statement when loading data into a table. It is used to specify whether the COPY statement should return an error if any of the rows in the file are invalid or if it should continue loading the valid rows. The VALIDATION_MODE parameter is only supported for COPY statements that load data from external stages1.
* The query in the question uses a data transformation query to load data from an internal stage. A data transformation query is a query that transforms the data during the load process, such as parsing JSON or XML data, applying functions, or joining with other tables2.
* According to the documentation, VALIDATION_MODE does not support COPY statements that transform data during a load. If the parameter is specified, the COPY statement returns an error1.
Therefore, option C is the correct answer.
References: : COPY INTO <table> : Transforming Data During a Load

NEW QUESTION # 95
Which security, governance, and data protection features require, at a MINIMUM, the Business Critical edition of Snowflake? (Choose two.)

A. Extended Time Travel (up to 90 days)
B. AWS, Azure, or Google Cloud private connectivity to Snowflake
C. Customer-managed encryption keys through Tri-Secret Secure
D. Periodic rekeying of encrypted data
E. Federated authentication and SSO

Answer: B,C

Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the security, governance, and data protection features that require, at a minimum, the Business Critical edition of Snowflake are:
* Customer-managed encryption keys through Tri-Secret Secure. This feature allows customers to manage their own encryption keys for data at rest in Snowflake, using a combination of three secrets: a master key, a service key, and a security password. This provides an additional layer of security and control over the data encryption and decryption process1.
* Periodic rekeying of encrypted data. This feature allows customers to periodically rotate the encryption keys for data at rest in Snowflake, using either Snowflake-managed keys or customer-managed keys. This enhances the security and protection of the data by reducing the risk of key compromise or exposure2.
The other options are incorrect because they do not require the Business Critical edition of Snowflake. Option A is incorrect because extended Time Travel (up to 90 days) is available with the Enterprise edition of Snowflake3. Option D is incorrect because AWS, Azure, or Google Cloud private connectivity to Snowflake is available with the Standard edition of Snowflake4. Option E is incorrect because federated authentication and SSO are available with the Standard edition of Snowflake5. References: Tri-Secret Secure | Snowflake Documentation, Periodic Rekeying of Encrypted Data | Snowflake Documentation, Snowflake Editions | Snowflake Documentation, Snowflake Network Policies | Snowflake Documentation, Configuring Federated Authentication and SSO | Snowflake Documentation

NEW QUESTION # 96
A media company needs a data pipeline that will ingest customer review data into a Snowflake table, and apply some transformations. The company also needs to use Amazon Comprehend to do sentiment analysis and make the de-identified final data set available publicly for advertising companies who use different cloud providers in different regions.
The data pipeline needs to run continuously ang efficiently as new records arrive in the object storage leveraging event notifications. Also, the operational complexity, maintenance of the infrastructure, including platform upgrades and security, and the development effort should be minimal.
Which design will meet these requirements?

A. Ingest the data using COPY INTO and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
B. Ingest the data into Snowflake using Amazon EMR and PySpark using the Snowflake Spark connector.
Apply transformations using another Spark job. Develop a python program to do model inference by leveraging the Amazon Comprehend text analysis API. Then write the results to a Snowflake table and create a listing in the Snowflake Marketplace to make the data available to other companies.
C. Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Create an external function to do model inference with Amazon Comprehend and write the final records to a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
D. Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.

Answer: C

Explanation:
This design meets all the requirements for the data pipeline. Snowpipe is a feature that enables continuous data loading into Snowflake from object storage using event notifications. It is efficient, scalable, and serverless, meaning it does not require any infrastructure or maintenance from the user. Streams and tasks are features that enable automated data pipelines within Snowflake, using change data capture and scheduled execution. They are also efficient, scalable, and serverless, and they simplify the data transformation process.
External functions are functions that can invoke external services or APIs from within Snowflake. They can be used to integrate with Amazon Comprehend and perform sentiment analysis on the data. The results can be written back to a Snowflake table using standard SQL commands. Snowflake Marketplace is a platform that allows data providers to share data with data consumers across different accounts, regions, and cloud platforms. It is a secure and easy way to make data publicly available to other companies.
Snowpipe Overview | Snowflake Documentation
Introduction to Data Pipelines | Snowflake Documentation
External Functions Overview | Snowflake Documentation
Snowflake Data Marketplace Overview | Snowflake Documentation

NEW QUESTION # 97
An Architect needs to design a data unloading strategy for Snowflake, that will be used with the COPY INTO
<location> command.
Which configuration is valid?

A. Location of files: Amazon S3
. File formats: CSV, JSON
. File encoding: Latin-1 (ISO-8859)
. Encryption: 128-bit
B. Location of files: Snowflake internal location
. File formats: CSV, XML
. File encoding: UTF-8
. Encryption: 128-bit
C. Location of files: Azure ADLS
. File formats: JSON, XML, Avro, Parquet, ORC
. Compression: bzip2
. Encryption: User-supplied key
D. Location of files: Google Cloud Storage
. File formats: Parquet
. File encoding: UTF-8
Compression: gzip

Answer: D

NEW QUESTION # 98
......

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Daniel Foster Daniel Foster

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