What types of worksheets can be created in Snowsight? (Select TWO).
Snowsight supports two worksheet types:SQL worksheetsandPython worksheets. SQL worksheets allow users to execute queries, create objects, and perform data analysis using ANSI SQL and Snowflake-specific extensions. Python worksheets, powered by Snowpark, allow users to write Python code that interacts directly with Snowflake tables, data frames, and machine learning workflows.
Java, Scala, and JavaScript are supported via Snowpark APIs or UDF development, but they cannot be used as worksheet languages. Worksheets are designed for interactive analysis, visualization, and iterative development, with native runtimes only for SQL and Python.
Thus, only SQL and Python worksheets can be created within Snowsight.
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What is the default Time Travel data retention period?
The default Time Travel retention period for most objects in Snowflake is1 day(24 hours). Time Travel enables access to historical versions of data after updates, deletes, or drops. It also allows cloning databases, schemas, and tables at previous points in time, and recovering dropped objects.
While Snowflake Enterprise Edition and higher tiers allow retention periods up to 90 days, this extended window is not the default---administrators must explicitly configure it for each table, schema, or database.
Retention periods of 7, 45, or 90 days are possible only with higher service editions; the default for all accounts and objects remains 1 day unless explicitly overridden.
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What is a benefit of using an external stage to load data into Snowflake?
External stages point to files in external cloud storage (S3, Azure Blob, GCS). Because the data is not stored inside Snowflake, the user avoids Snowflake storage charges, which can significantly reduce cost for large staging datasets.
External stages do not automatically delete files, are not inherently more secure than internal stages, and still count as database objects even though they reference external storage.
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What command can be used to load data from an external stage to a table?
TheCOPY INTOcommand is Snowflake's primary bulk-loading mechanism for ingesting data from stages (internal or external) into tables. It can read from Amazon S3, Azure Blob Storage, Google Cloud Storage, or internal Snowflake stages. COPY INTO supports file formats (CSV, JSON, Parquet), pattern matching, error handling, transformations, and validation modes.
PUT uploads filesfrom a local machineto an internal stage---not from stage to table.
GET downloads files from an internal stage to a local system.
INSERT INTO is for row-by-row inserts and is not designed for large file ingestion.
Therefore, COPY INTO is the correct and recommended method for loading stage files into Snowflake tables.
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What is the purpose of a role hierarchy in Snowflake?
Role hierarchy in Snowflake allows one role to inherit the privileges of another. By granting roles to other roles, Snowflake enables scalable, maintainable access control. Higher-level roles grant privileges downward, allowing administrators to create layered access structures. This hierarchy simplifies permission management across teams and environments. It has no relation to SQL sequencing, network settings, or data storage.
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