What is a key difference between the Snowflake CLI and SnowSQL?
Answer(s): B
The Snowflake CLI is designed for managing Snowflake resources, applications, and development workflows, while SnowSQL is a command-line client primarily used to execute SQL statements and perform database operations.
Which services are handled within the Cloud Services layer? (Choose two.)
Answer(s): A,E
The Cloud Services layer is responsible for coordinating system-wide services such as authentication and access control, as well as managing metadata, which includes object definitions, query history, and optimization information.
A user is automating a data pipeline using the Snowflake CLI and needs to pass variables into SQL scripts.Which variable templating syntaxes should be used? (Choose two.)
Answer(s): B,C
The Snowflake CLI supports variable templating using both legacy-style variables and Jinja templating, enabling dynamic parameterization of SQL scripts within automation workflows.
What is the MINIMUM Snowflake edition needed to apply 90 days of Time Travel to an object?
Enterprise Edition supports extended Time Travel retention beyond the default limits, allowing up to 90 days for data recovery on supported objects.
Which objects can be recovered after being dropped? (Choose two.)
Answer(s): D,E
Permanent objects and materialized views support Time Travel and Fail-safe, allowing them to be recovered after being dropped within the retention period.
How does Snowflake support storage for external tables?
Snowflake does not store the actual data of external tables; it stores only the metadata that defines the structure and location of the external data, which remains in external storage.
Which Snowflake features support the ability to write to a Git repository?
Answer(s): D
Streamlit applications, workspaces, and notebooks are part of Snowflake's development environment that integrates with Git, allowing users to write, version, and synchronize code directly with a Git repository.
A Snowflake Practitioner is tasked with designing a data lakehouse architecture that requires:1. Support for ACID transactions to ensure data consistency2. The ability to evolve schemas over time without rewriting existing data3. Efficient querying capabilities on large datasetsWhich table type meets these requirements?
Iceberg tables provide ACID transaction support, allow schema evolution without rewriting existing data, and enable efficient querying of large datasets stored in a lakehouse architecture.
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