The correct answer is C. To record changes made to table data and metadata, so that the changed data can be processed .
A Snowflake stream is a change tracking object. It records data manipulation language, or DML, changes made to a source table, including inserts, updates, and deletes. Streams are commonly used with tasks to build incremental data pipelines.
Why C is correct:
Streams allow users to identify what changed in a table since the stream was last consumed. This makes it possible to process only changed rows rather than reprocessing the entire table.
A stream exposes metadata columns such as:
METADATA$ACTION
METADATA$ISUPDATE
METADATA$ROW_ID
These metadata columns help identify the type of change and the affected row.
Why the other options are incorrect:
A). This describes real-time ingestion, which is closer to Snowpipe, connectors, or streaming ingestion rather than streams.
B). Snowflake streams are not media streaming services.
D). This describes a general streaming data processing system, but a Snowflake stream itself does not process data. It records changes so other SQL processes can consume them.
Official Snowflake documentation reference:
Snowflake documentation describes streams as objects that record DML changes made to tables, including metadata about each change, so the changes can be consumed in downstream processing.
Reference: Snowflake Documentation - Streams; Snowflake Documentation - Stream metadata columns; SnowPro Core Study Guide - SQL and Snowflake Objects.
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The COPY INTO SQL command with the option SINGLE=FALSE is used to unload data into multiple files.
This option allows the data to be split into multiple files during the unload process. References: SnowPro Core Certification COPY INTO SQLcommand unload multiple files

For the ALLOWED VALUES tag property, the maximum number of possible string values for a single tag is
256. This allows for a wide range of values to be assigned to a tag when it is set on an object

For directory tables, a named external stage allows for the automatic refreshing of metadata. This capability is particularly useful when dealing with files stored on external storage services (like Amazon S3, Google Cloud Storage, or Azure Blob Storage) and accessed through Snowflake. The external stage references these files, and the directory table ' s metadata can be automatically updated to reflect changes in the underlying files.
References:
Snowflake Documentation: External Stages

In Snowflake, Secure User-Defined Functions (UDFs) can be shared with other accounts using Snowflake ' s data sharing feature. This allows different Snowflake accounts to securely execute the UDFs without having direct access to the underlying data the functions operate on, ensuring privacy and security. The sharing is facilitated through shares created in Snowflake, which can contain Secure UDFs along with other database objects like tables and views.
References: Snowflake Documentation on Data Sharing and Secure UDFs