Multi-Factor Authentication (MFA) provides increased login security for users connecting to Snowflake. Snowflake’s MFA is powered by Duo Security service, which adds an additional layer of security during the login process.

 In Snowflake, a user with the SECURITYADMIN role or higher can activate and enforce a network policy for all users in an account. Additionally, a role that has ownership of the network policy can also activate and enforce it

The TABLE_STORAGE_METRICS metadata table stores the storage utilization information, including for tables that have been dropped but are still incurring storage costs2.

The OWNERSHIP privilege is unique in that it must be granted by one role to another and cannot be revoked. This ensures that the transfer of ownership is deliberate and permanent, reflecting the importance of ownership in managing access and permissions.

The Query Profile statistics that indicate intermediate results do not fit in memory are the bytes spilled to local storage and bytes spilled to remote storage2.

When the data retention period is changed at the schema level, all child objects that do not have an explicit retention period setwill inherit the new retention period from the schema4.

In owner’s rights stored procedures, certain commands are restricted to maintain security and integrity. The SHOW and DESCRIBE commands are limited because they can reveal metadata and structure information that may not be intended for all roles. 

A directory table in Snowflake is used to store file-level metadata about the data files in a stage. It is conceptually similar to an external table and provides information such as file size, last modified timestamp, and file URL. References: [COF-C03] SnowPro Core Certification Exam Study Guide

The FLATTEN function can be used with the recursive argument to return a list of distinct key names in all nested elements within an object. This function is particularly useful for working with semi-structured data in Snowflake

A Stream object in Snowflake is used for change data capture (CDC), which records data manipulation language (DML) changes made to tables, including inserts, updates, and deletes3.

When federated authentication is activated in Snowflake, users authenticate via an external identity provider (IdP) rather than using Snowflake-managed credentials. Therefore, a user with a password defined by Snowflake will be unable to enter a password and must use their IdP credentials to log in.

QUSTION NO:579

What value provides information about disk usage for operations where intermediate results do not fit in memory in a Query Profile?

A. IO

B. Network

C. Pruning

D. Spilling

Answer: D

In Snowflake, when a query execution requires more memory than what is available, Snowflake handles these situations by spilling the intermediate results to disk. This process is known as " spilling. " The Query Profile in Snowflake includes a metric that helps users identify when and how much data spilling occurs during the execution of a query. This information is crucial for optimizing queries as excessive spilling can significantly slow down query performance. The value that provides this information about disk usage due to intermediate results not fitting in memory is appropriately labeled as " Spilling " in the Query Profile.

Snowflake’s Time Travel feature is used for the maintenance of historical data, allowing users to access andrestore data that has been changed or deleted within a defined period4.

 When the DROP MANAGED ACCOUNT command is executed in Snowflake, it removes the managed account, including all objects created within the account, and access to the account is immediately restricted2.

The LATERAL modifier for the FLATTEN function allows joining information outside the object (such as other columns in the source table) with the flattened data, creating a lateral view that correlates with the preceding tables in the FROM clause2345. References: [COF-C03] SnowPro Core Certification Exam Study Guide

The Snowflake command to unload the result of a query to a single file is COPY INTO < internal stage > with SINGLE = TRUE followed by a GET command to download the file. This command unloads the query result into a single file in the specified internal stage

When a running virtual warehouse in Snowflake issuspended and then restarted, the minimum amount of time it will incur charges for is 60 seconds2.

 Storing JSON data in a table with a VARIANT data type is optimal for querying because it allows Snowflake to leverage its semi-structured data capabilities. This approach enables efficient storage and querying without the need for flattening the data, which can be performance-intensive1.

 For loading data into Snowflake via Snowpipe, the recommended compressed file size is between 100-250 MB. This size range is optimal for balancing the performance of parallel processing and minimizing the overhead associated with handling many small files2.

The LOGIN_HISTORY view in the ACCOUNT_USAGE schema provides information about login attempts, including both successful and failed logins. This view can be used to review the failed login attempts of a specific user for the past 30 days. References: [COF-C03] SnowPro Core Certification Exam Study Guide

Snowflake supports the use of external stages with Amazon Web Services (AWS), Microsoft Azure Cloud, and Google Cloud Platform (GCP). These platforms allow users to stage data externally and integrate with Snowflake for data loading operations