What are computer language considerations when using Snowflake interfaces? (Select TWO).
Answer(s): A,C
Snowflake Notebooks support both SQL and Python as executable cell types. This means that users can create notebook cells written in Python for programmatic data processing and modeling, and in SQL for declarative querying and transformation. Because of this, the statements "Notebook cells can be written in Python" and "Notebook cells can be written in SQL" are both correct.Snowflake databases do not natively execute queries written in Scala; Scala is supported via Snowpark APIs for application code, not as a direct query language. Worksheets in Snowsight are primarily SQL-based and also support procedural constructs (e.g., Snowflake Scripting), so the phrase "only in SQL" is not a precise or complete characterization. Dashboards in Snowsight are created using SQL-backed visualizations and built-in UI components; JavaScript is not a supported authoring language inside the native dashboarding layer. Therefore, options B, D, and E are not correct in this context.
What Snowflake object is used to store data?
Answer(s): A
A table is the core Snowflake object used to store structured data. Tables persist rows and columns in Snowflake's storage layer, which internally uses compressed, columnar micro-partitions managed by the platform. Tables can be permanent, transient, or temporary, but in every case, they are the primary objects that hold the actual data.A virtual warehouse is a compute resource used to process queries and perform operations; it does not store user data. A stored procedure contains executable logic (such as complex workflows or procedural code) but does not serve as a data container. A view is a logical object that presents the results of a saved query; it references underlying tables and does not store its own data. As a result, "Table" is the correct answer.
Where is unstructured data stored in Snowflake?
Answer(s): B
Unstructured data such as PDF files, images, and other binary documents is stored in stages in Snowflake. These stages may be internal stages, which Snowflake manages directly, or external stages, which reference external cloud storage such as Amazon S3, Azure Blob Storage, or Google Cloud Storage. Stages are the designed mechanism for storing and accessing unstructured files so that they can be processed with functions like PARSE_DOCUMENT or accessed via directory tables.External tables are used to query structured or semi-structured data (for example, Parquet or JSON) stored in external locations, not to store raw unstructured binary content. The Cloud Services layer coordinates metadata, security, and query services; it does not store user data. Tables with a single VARCHAR column might be used as an improvised approach for small text blobs, but this is not the native or recommended method for managing unstructured data at scale.
What is the name of Snowflake's default web-based interface?
Answer(s): C
Snowsight is the default web-based interface for Snowflake. It provides a graphical, browser-based environment to write and run SQL and Python, manage and explore database objects, create visualizations and dashboards, monitor query and warehouse activity, and collaborate via worksheets. It has replaced the Classic Console as the default UI for new Snowflake accounts.SnowSQL is a command-line client used to connect to Snowflake from a terminal and execute SQL statements. Snowpark is a developer framework that supports writing data applications in languages like Python, Java, and Scala, but it is not a UI. "Snowflake CLI" refers to command-line tooling and automation utilities, again not a graphical web interface.
What task can be performed on the Snowsight Schema Details page?
On the Snowsight Schema Details page, one of the supported operations is renaming the schema. The UI exposes controls that allow users with appropriate privileges to change the schema name, which can help maintain consistent naming conventions or reflect project reorganizations.Sharing data with other accounts is typically done using secure shares at the database or object level, not from a simple "Share this schema" function on the Schema Details page. Truncation is a table- level operation (e.g., TRUNCATE TABLE), not something that applies at the schema level. Metrics visible on the Schema Details page (such as object counts or storage usage) are informational and not directly editable; they are derived from system metadata.
What is the impact of enabling auto-suspend on a Snowflake virtual warehouse?
When auto-suspend is enabled on a virtual warehouse, Snowflake automatically suspends (stops) the warehouse after it has been idle for the configured period of time. Once suspended, the warehouse stops consuming compute credits, thereby reducing costs, since Snowflake bills only for active compute usage. When new queries arrive, auto-resume (if enabled) restarts the warehouse automatically.Auto-suspend does not change the warehouse size; scaling up or down is a separate configuration. The warehouse is not dropped--its metadata and settings remain intact. Costs may be reduced and made more efficient but are not guaranteed to "stabilize month-to-month," as the bill still depends on actual usage and workload patterns.
What parameter is used to define how long Time Travel can be used to access a table?
The DATA_RETENTION_TIME_IN_DAYS parameter controls the Time Travel retention period for Snowflake objects such as tables, schemas, and databases. It specifies the number of days that historical data (prior versions of rows or dropped objects) is retained and accessible via Time Travel. Within this retention window, users can query data "as of" a previous time, restore dropped objects, or clone objects at a historical point.DATE_OUTPUT_FORMAT determines the display format for date values and is unrelated to historical retention. TIMEZONE affects how timestamps are interpreted and displayed, not how long data history is preserved. USE_CACHED_RESULT governs whether Snowflake may return cached query results, not Time Travel behavior.
What filter can be used when searching for data products on the Snowflake Marketplace?
On the Snowflake Marketplace, users can apply a Price filter when searching for data products. This filter helps distinguish between free offerings and paid listings, making it easier to align data acquisition with budget and commercial terms. Marketplace metadata includes pricing information that this filter uses to refine search results.Dataset "Size" is not exposed as a primary Marketplace search filter. "Compatibility" is implied, as all Marketplace products are consumable within Snowflake. "Performance" is not a filterable attribute, because performance is influenced mainly by the consumer's compute configuration and query design, rather than a fixed property of the Marketplace listing.
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