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| Section | Weight | Objectives |
|---|---|---|
| Data Engineering | 25% | - Data Transformation
|
| Performance Optimization | 20% | - Query Performance
|
| Accounts and Security | 25% | - Governance and Compliance
|
| Snowflake Architecture | 30% | - Platform Architecture Design
|
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NEW QUESTION # 23
What Snowflake features should be leveraged when modeling using Data Vault?
Answer: A
Explanation:
These two features are relevant for modeling using Data Vault on Snowflake. Data Vault is a data modeling approach that organizes data into hubs, links, and satellites. Data Vault is designed to enable high scalability, flexibility, and performance for data integration and analytics. Snowflake is a cloud data platform that supports various data modeling techniques, including Data Vault. Snowflake provides some features that can enhance the Data Vault modeling, such as:
* Snowflake's support of multi-table inserts into the data model's Data Vault tables. Multi-table inserts (MTI) are a feature that allows inserting data from a single query into multiple tables in a single DML statement. MTI can improve the performance and efficiency of loading data into Data Vault tables, especially for real-time or near-real-time data integration. MTI can also reduce the complexity and maintenance of the loading code, as well as the data duplication and latency12.
* Scaling up the virtual warehouses will support parallel processing of new source loads. Virtual warehouses are a feature that allows provisioning compute resources on demand for data processing.
Virtual warehouses can be scaled up or down by changing the size of the warehouse, which determines the number of servers in the warehouse. Scaling up the virtual warehouses can improve the performance
* and concurrency of processing new source loads into Data Vault tables, especially for large or complex data sets. Scaling up the virtual warehouses can also leverage the parallelism and distribution of Snowflake's architecture, which can optimize the data loading and querying34.
References:
* Snowflake Documentation: Multi-table Inserts
* Snowflake Blog: Tips for Optimizing the Data Vault Architecture on Snowflake
* Snowflake Documentation: Virtual Warehouses
* Snowflake Blog: Building a Real-Time Data Vault in Snowflake
NEW QUESTION # 24
An Architect is designing an architecture that must meet the following requirements:
* Use Tri-Secret Secure
* Share some information stored in a view with another Snowflake customer
* Hide portions of sensitive information in columns
* Use zero-copy cloning to refresh non-production from production
Which design elements must be implemented? (Select THREE).
Answer: A,B,F
Explanation:
Tri-Secret Secure is only available in Snowflake Business Critical edition or higher, making that edition mandatory to satisfy the first requirement (Answer B). Secure views are required when sharing data with another Snowflake customer to ensure that underlying table data, logic, and metadata are protected and governed during Secure Data Sharing (Answer C). To hide or reveal portions of sensitive data at query time based on role or policy, Dynamic Data Masking is the appropriate Snowflake feature (Answer E).
Row access policies control row-level visibility but do not mask column values. The Enterprise edition does not support Tri-Secret Secure, making it insufficient for the stated requirements. Materialized views are unrelated to security or data masking and introduce unnecessary storage overhead.
This question integrates multiple SnowPro Architect domains-security, governance, sharing, and environment management-and tests the architect's ability to select the minimal set of Snowflake features that collectively meet complex compliance and operational requirements.
=========
NEW QUESTION # 25
What is a characteristic of Role-Based Access Control (RBAC) as used in Snowflake?
Answer: A,C
Explanation:
Role-Based Access Control (RBAC) is the Snowflake Access Control Framework that allows privileges to be granted by object owners to roles, and roles, in turn, can be assigned to users to restrict or allow actions to be performed on objects. A characteristic of RBAC as used in Snowflake is:
* Privileges can be granted at the database level and can be inherited by all underlying objects. This means that a role that has a certain privilege on a database, such as CREATE SCHEMA or USAGE, can also perform the same action on any schema, table, view, or other object within that database, unless explicitly revoked. This simplifies the access control management and reduces the number of grants required.
* A user can create managed access schemas to support future grants and ensure only schema owners can grant privileges to other roles. This means that a user can create a schema with the MANAGED ACCESS option, which changes the default behavior of object ownership and privilege granting within the schema. In a managed access schema, object owners lose the ability to grant privileges on their objects to other roles, and only the schema owner or a role with the MANAGE GRANTS privilege can do so. This enhances the security and governance of the schema and its objects.
The other options are not characteristics of RBAC as used in Snowflake:
* A user can use a "super-user" access along with securityadmin to bypass authorization checks and access all databases, schemas, and underlying objects. This is not true, as there is no such thing as a
"super-user" access in Snowflake. The securityadmin role is a predefined role that can manage users and roles, but it does not have any privileges on any database objects by default. To access any object, the securityadmin role must be explicitly granted the appropriate privilege by the object owner or another role with the grant option.
* A user can create managed access schemas to support current and future grants and ensure only object owners can grant privileges to other roles. This is not true, as this contradicts the definition of a managed access schema. In a managed access schema, object owners cannot grant privileges on their objects to other roles, and only the schema owner or a role with the MANAGE GRANTS privilege can do so.
References:
* Overview of Access Control
* A Functional Approach For Snowflake's Role-Based Access Controls
* Snowflake Role-Based Access Control simplified
* Snowflake RBAC security prefers role inheritance to role composition
* Overview of Snowflake Role Based Access Control
NEW QUESTION # 26
How does a standard virtual warehouse policy work in Snowflake?
Answer: A
NEW QUESTION # 27
A company stores customer data in Snowflake and must protect Personally Identifiable Information (PII) to meet strict regulatory requirements.
What should an Architect do?
Answer: A
Explanation:
Tag-based masking policies provide a scalable and centralized way to protect PII across many tables and schemas (Answer B). By tagging columns that contain PII and associating masking policies with those tags, Snowflake automatically enforces masking rules wherever the tagged columns appear. This approach reduces administrative overhead and ensures consistent enforcement as schemas evolve.
Row access policies control row visibility, not column masking. Secure views and table separation can protect data but introduce significant maintenance complexity and do not scale well across large environments.
Snowflake best practices-and the SnowPro Architect exam-emphasize tag-based governance for sensitive data.
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NEW QUESTION # 28
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