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| Section | Weight | Objectives |
|---|---|---|
| Performance Optimization | 20% | - Cost optimization and resource management - Virtual warehouse configuration and sizing - Clustering and partitioning strategies - Query performance tuning |
| Snowflake Architecture | 30% | - Object hierarchy and architectural impact - Data modeling and use cases - Data sharing architecture design - Development lifecycle and workload support - Data protection and recovery strategies |
| Accounts and Security | 25% | - Account and database strategy design - Security principles and implementation scenarios - Security, compliance and governance architecture |
| Data Engineering | 25% | - Data loading and unloading solutions - Transformation and processing frameworks - Data pipeline and integration design |
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NEW QUESTION # 215
An Architect is designing a data lake with Snowflake. The company has structured, semi-structured, and unstructured data. The company wants to save the data inside the data lake within the Snowflake system. The company is planning on sharing data among its corporate branches using Snowflake data sharing.
What should be considered when sharing the unstructured data within Snowflake?
Answer: C
Explanation:
When sharing unstructured data within Snowflake, using a scoped URL is recommended. Scoped URLs provide temporary access to staged files without granting privileges to the stage itself, enhancing security. The URL expires when the persisted query result period ends, which is currently set to 24 hours. This approach is suitable for sharing unstructured data over secure views within Snowflake's data sharing framework.
References: The answer is based on Snowflake's official documentation regarding the sharing of unstructured data and the use of scoped URLs1.
NEW QUESTION # 216
A healthcare company is deploying a Snowflake account that may include Personal Health Information (PHI).
The company must ensure compliance with all relevant privacy standards.
Which best practice recommendations will meet data protection and compliance requirements? (Choose three.)
Answer: A,B,E
Explanation:
* A healthcare company that handles PHI data must ensure compliance with relevant privacy standards, such as HIPAA, HITRUST, and GDPR. Snowflake provides several features and best practices to help customers meet their data protection and compliance requirements1.
* One best practice recommendation is to use, at minimum, the Business Critical edition of Snowflake. This edition provides the highest level of data protection and security, including end-to-end encryption with customer-managed keys, enhanced object-level security, and HIPAA and HITRUST compliance2. Therefore, option A is correct.
* Another best practice recommendation is to create Dynamic Data Masking policies and apply them to columns that contain PHI. Dynamic Data Masking is a feature that allows masking or redacting sensitive data based on the current user's role. This way, only authorized users can view the unmasked data, while others will see masked values, such as NULL, asterisks, or random characters3. Therefore, option B is correct.
* A third best practice recommendation is to use the External Tokenization feature to obfuscate sensitive data. External Tokenization is a feature that allows replacing sensitive data with tokens that are
* generated and stored by an external service, such as Protegrity. This way, the original data is never stored or processed by Snowflake, and only authorized users can access the tokenized data through the external service4. Therefore, option D is correct.
* Option C is incorrect, because the Internal Tokenization feature is not available in Snowflake. Snowflake does not provide any native tokenization functionality, but only supports integration with external tokenization services4.
* Option E is incorrect, because rewriting SQL queries to eliminate projections of PHI data based on current_role() is not a best practice. This approach is error-prone, inefficient, and hard to maintain. A better alternative is to use Dynamic Data Masking policies, which can automatically mask data based on the user's role without modifying the queries3.
* Option F is incorrect, because avoiding sharing data with partner organizations is not a best practice.
Snowflake enables secure and governed data sharing with internal and external consumers, such as business units, customers, or partners. Data sharing does not involve copying or moving data, but only granting access privileges to the shared objects. Data sharing can also leverage Dynamic Data Masking and External Tokenization features to protect sensitive data5.
References: : Snowflake's Security & Compliance Reports : Snowflake Editions : Dynamic Data Masking : External Tokenization : Secure Data Sharing
NEW QUESTION # 217
Assuming all Snowflake accounts are using an Enterprise edition or higher, in which development and testing scenarios would be copying of data be required, and zero-copy cloning not be suitable? (Select TWO).
Answer: B,E
Explanation:
Zero-copy cloning is a feature that allows creating a clone of a table, schema, or database without physically copying the data. Zero-copy cloning is suitable for scenarios where the cloned object needs to have the same data and metadata as the original object, and where the cloned object does not need to be modified or updated frequently. Zero-copy cloning is also suitable for scenarios where the cloned object needs to be shared within the same Snowflake account or across different accounts in the same cloud region2 However, zero-copy cloning is not suitable for scenarios where the cloned object needs to have different data or metadata than the original object, or where the cloned object needs to be modified or updated frequently.
Zero-copy cloning is also not suitable for scenarios where the cloned object needs to be shared across different accounts in different cloud regions. In these scenarios, copying of data would be required, either by using the COPY INTO command or by using data sharing with secure views3 The following are examples of development and testing scenarios where copying of data would be required, and zero-copy cloning would not be suitable:
* Developers create their own datasets to work against transformed versions of the live data. This scenario requires copying of data because the developers need to modify the data or metadata of the cloned object to perform transformations, such as adding, deleting, or updating columns, rows, or values. Zero-copy cloning would not be suitable because it would create a read-only clone that shares the same data and metadata as the original object, and any changes made to the clone would affect the original object as well4
* Data is in a production Snowflake account that needs to be provided to Developers in a separate
* development/testing Snowflake account in the same cloud region. This scenario requires copying of data because the data needs to be shared across different accounts in the same cloud region. Zero-copy cloning would not be suitable because it would create a clone within the same account as the original object, and it would not allow sharing the clone with another account. To share data across different accounts in the same cloud region, data sharing with secure views or COPY INTO command can be used5 The following are examples of development and testing scenarios where zero-copy cloning would be suitable, and copying of data would not be required:
* Production and development run in different databases in the same account, and Developers need to see production-like data but with specific columns masked. This scenario can use zero-copy cloning because the data needs to be shared within the same account, and the cloned object does not need to have different data or metadata than the original object. Zero-copy cloning can create a clone of the production database in the development database, and the clone can have the same data and metadata as the original database. To mask specific columns, secure views can be created on top of the clone, and the developers can access the secure views instead of the clone directly6
* Developers create their own copies of a standard test database previously created for them in the development account, for their initial development and unit testing. This scenario can use zero-copy cloning because the data needs to be shared within the same account, and the cloned object does not need to have different data or metadata than the original object. Zero-copy cloning can create a clone of the standard test database for each developer, and the clone can have the same data and metadata as the original database. The developers can use the clone for their initial development and unit testing, and any changes made to the clone would not affect the original database or other clones7
* The release process requires pre-production testing of changes with data of production scale and complexity. For security reasons, pre-production also runs in the production account. This scenario can use zero-copy cloning because the data needs to be shared within the same account, and the cloned object does not need to have different data or metadata than the original object. Zero-copy cloning can create a clone of the production database in the pre-production database, and the clone can have the same data and metadata as the original database. The pre-production testing can use the clone to test the changes with data of production scale and complexity, and any changes made to the clone would not affect the original database or the production environment8 References:
* 1: SnowPro Advanced: Architect | Study Guide 9
* 2: Snowflake Documentation | Cloning Overview
* 3: Snowflake Documentation | Loading Data Using COPY into a Table
* 4: Snowflake Documentation | Transforming Data During a Load
* 5: Snowflake Documentation | Data Sharing Overview
* 6: Snowflake Documentation | Secure Views
* 7: Snowflake Documentation | Cloning Databases, Schemas, and Tables
* 8: Snowflake Documentation | Cloning for Testing and Development
* : SnowPro Advanced: Architect | Study Guide
* : Cloning Overview
* : Loading Data Using COPY into a Table
* : Transforming Data During a Load
* : Data Sharing Overview
* : Secure Views
* : Cloning Databases, Schemas, and Tables
* : Cloning for Testing and Development
NEW QUESTION # 218
The data share exists between a data provider account and a data consumer account. Five tables from the provider account are being shared with the consumer account. The consumer role has been granted the imported privileges privilege.
What will happen to the consumer account if a new table (table_6) is added to the provider schema?
Answer: C
Explanation:
When a new table (table_6) is added to a schema in the provider's account that is part of a data share, the consumer will not automatically see the new table. The consumer will only be able to access the new table once the appropriate privileges are granted by the provider. The correct process, as outlined in option D, involves using the provider's ACCOUNTADMIN role to grant USAGE privileges on the database and schema, followed by SELECT privileges on the new table, specifically to the share that includes the consumer's database. This ensures that the consumer account can access the new table under the established data sharing setup.
References:
Snowflake Documentation on Managing Access Control
Snowflake Documentation on Data Sharing
NEW QUESTION # 219
You have an inventory table. You created two views on this table. The views look like as below
CREATE VIEW NON_SECURE_INVENTORY AS
SELECT BIBNUMBER, TITLE, AUTHOR,ISBN
FROM INVENTORY
WHERE BIBNUMBER IN(511784,511805,511988,512044,512052,512063);
CREATE SECURE VIEW SECURE_INVENTORY AS
SELECT BIBNUMBER, TITLE, AUTHOR,ISBN
FROM INVENTORY
WHERE BIBNUMBER IN(511784,511805,511988,512044,512052,512063);
You ran the below queries
ALTER SESSION SET USE_CACHED_RESULT=FALSE;--This is to ensure that we do not retrieve from query cache
SELECT * FROM NON_SECURE_INVENTORY WHERE BIBNUMBER =511784; SELECT * FROM SECURE_INVENTORY WHERE BIBNUMBER =511784;
The query profile for the first query looks as below
However, the query profile for the second one looks like as below
Both the views use the same columns from the same underlying view. So, why is this difference in query profiles.
Answer: A
NEW QUESTION # 220
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