Snowflake SnowPro Core Practice Test - Questions Answers, Page 49

To temporarily bypass a network policy by configuring the user object property MINS_TO_BYPASS_NETWORK_POLICY, the USERADMIN role should be used. This role has the necessary privileges to modify user properties, including setting a temporary bypass for network policies, which can be crucial for enabling access under specific circumstances without permanently altering the network security configuration.

Snowflake Documentation: User Management

A cached MFA token is valid for up to four hours. https://docs.snowflake.com/en/user-guide/security-mfa#using-mfa-token-caching-to-minimize-the-number-of-prompts-during-authentication-optional

The Virtual Private Snowflake (VPS) edition offers the highest level of security for organizations with the strictest security requirements. This edition provides a dedicated and isolated instance of Snowflake, including enhanced security features and compliance certifications to meet the needs of highly regulated industries or any organization requiring the utmost in data protection and privacy.

Snowflake Documentation: Snowflake Editions

Snowflake recommends enhancing the granularity and management of privileges by creating and utilizing custom roles. When additional privileges are needed beyond those provided by the system-defined roles for a virtual warehouse or any other resource, these privileges should be granted to a custom role. This approach allows for more precise control over access rights and the ability to tailor permissions to the specific needs of different user groups or applications within the organization, while also maintaining the integrity and security model of system-defined roles.

Snowflake Documentation: Roles and Privileges

The OBJECT_CONSTRUCT function in Snowflake is used to convert rows in a relational table into a single VARIANT column that represents each row as a JSON object. This function dynamically creates a JSON object from a list of key-value pairs, where each key is a column name and each value is the corresponding column value for a row. This is particularly useful for aggregating and transforming structured data into semi-structured JSON format for further processing or analysis.

Snowflake Documentation: Semi-structured Data Functions

Snowflake supports a variety of file formats for unloading semi-structured data, among which Parquet and Newline Delimited JSON (NDJSON) are two widely used formats.

B . Binary file in Parquet: Parquet is a columnar storage file format optimized for large-scale data processing and analysis. It is especially suited for complex nested data structures.

D . Newline Delimited JSON (NDJSON): This format represents JSON records separated by newline characters, facilitating the storage and processing of multiple, separate JSON objects in a single file.

These formats are chosen for their efficiency and compatibility with data analytics tools and ecosystems, enabling seamless integration and processing of exported data.

Snowflake Documentation: Data Unloading

The layer of Snowflake's architecture associated with virtual warehouses is the Query Processing layer. Virtual warehouses in Snowflake are dedicated compute clusters that execute SQL queries against the stored data. This layer is responsible for the entire query execution process, including parsing, optimization, and the actual computation. It operates independently of the storage layer, enabling Snowflake to scale compute and storage resources separately for efficiency and cost-effectiveness.

Snowflake Documentation: Snowflake Architecture

Tri-secret secure encryption is a security model employed by Snowflake that involves combining a customer-managed key with a Snowflake-managed key to create a composite key for encrypting data. This model enhances data security by requiring both the customer-managed key and the Snowflake-managed key to decrypt data, thus ensuring that neither party can access the data independently. It represents a balanced approach to key management, leveraging both customer control and Snowflake's managed services for robust data encryption.

Snowflake Documentation: Encryption and Key Management

When creating a CSV file format in Snowflake and the requirement is to wrap columns by single quotes or double quotes, the FIELD_OPTIONALLY_ENCLOSED_BY parameter should be used in the file format specification. This parameter allows you to define a character (either a single quote or a double quote) that can optionally enclose each field in the CSV file, providing flexibility in handling fields that contain special characters or delimiters as part of their data.

Snowflake Documentation: CSV File Format