SOL-C01 Snowflake SnowPro Associate: Platform Certification Exam Free Practice Exam Questions (2025 Updated)

The USE SCHEMA command sets the active schema context for the current session. After it is executed, any unqualified object names (for example, SELECT * FROM my_table) are resolved within that schema. This reduces the need to fully qualify object names with database and schema each time and ensures that statements reference the expected logical container.

CREATE SCHEMA is used to create a new schema. ALTER SCHEMA and GRANT OWNERSHIP are used to modify schema properties or transfer ownership, respectively. USE SCHEMA does not alter structure or ownership; it simply changes the context in which subsequent SQL statements are interpreted.

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Snowflake warehouse sizes followT-shirt sizing, each representing a doubling of compute resources relative to the previous size. Valid Snowflake warehouse sizes includeX-Small,Small,Medium,Large, and up to6X-Large.

X-Smallis the smallest supported warehouse size and is commonly used for light data processing, development tasks, and low-volume operations.

Smalldoubles the compute capacity of X-Small, providing better performance for moderate workloads.

Mediumcontinues scaling upward, offering increased CPU, memory, and parallelism for heavier analytics or transformation workloads.

Tinyis not a Snowflake warehouse size. Snowflake never exposes a warehouse smaller than X-Small, ensuring consistent minimum compute capabilities.

These standardized size tiers allow predictable resource scaling and cost forecasting.

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TheSKIP_HEADERoption instructs Snowflake to ignore a defined number of initial rows, typically the column header row in CSV files. For example:

CREATE FILE FORMAT my_fmt

TYPE='CSV'

SKIP_HEADER=1;

When used with COPY INTO, Snowflake loads only the actual data rows while excluding header metadata. This prevents header values from being inserted as data and ensures consistent row structure.

Other options:

SKIP_BLANK_LINEScontrols handling of empty rows, not headers.

Snowflake does not auto-generate column names from header rows; table schemas must be predefined.

Including header rows as data is undesirable and incorrect in most pipelines.

Thus, SKIP_HEADER is used exclusively to omit header rows during ingestion.

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Unstructured data refers to content that lacks a predefined schema or consistent structural pattern. It cannot be represented naturally in tabular or hierarchical formats without extraction or transformation. Snowflake supports unstructured data through external tables and native features allowing storage and machine learning analyses.Images,videos, andPDFsfall into this category because they contain raw multimedia or document content without intrinsic row/column structure, often requiring OCR, video/audio processing, or content extraction. In contrast, JSON is semi-structured, containing keys, hierarchical structures, and metadata that Snowflake’s VARIANT type can interpret directly. Unstructured data is becoming increasingly important for AI-driven workloads, enabling use cases such as OCR with PARSE_DOCUMENT, deep-learning analysis of images and video, and document intelligence tasks.

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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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When you preview a table in Snowsight, Snowflake returns up to the first 100 rows of the table’s data. This preview is designed for quick inspection of the table’s contents and structure without requiring the user to manually write a SELECT query. The preview interface allows basic exploration such as scrolling, simple sorting, and viewing column metadata.

Tables are not “stored” in a specific virtual warehouse; warehouses provide compute only. The table definition (DDL) can be viewed in the Table Details section but is not the main output of the Preview action. Snowsight does not natively generate an Entity Relationship (ER) diagram for the table as part of the preview.

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The Snowsight Query Profile is a powerful diagnostic tool that provides a visual breakdown of how Snowflake executed a query. Its primary purpose is to help users visualize and analyze query performance. It displays execution steps, including scan operations, join strategies, pruning results, aggregation methods, and data movement between processing nodes.

The profile shows metrics such as execution time per step, partition pruning effectiveness, bytes scanned, and operator relationships. This allows developers, analysts, and DBAs to identify bottlenecks—such as unnecessary full-table scans, non-selective filters, or inefficient joins—and tune SQL accordingly.

Query Profile does not execute queries; execution happens in worksheets or programmatic interfaces. It does not create objects or manage data loading; those tasks involve separate SQL commands and UI interfaces.

Overall, Query Profile is essential for performance tuning, helping teams reduce compute costs, optimize warehouse sizing, and improve query efficiency.

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AUTO_SUSPEND minimizes cost by suspending compute after a specified idle period.

It prevents unnecessary credit consumption while ensuring compute resumes automatically when needed.

Performance improvements depend on warehouse size, not suspension settings.

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Snowflake'sINFORMATION_SCHEMAcontains metadata views about databases, schemas, tables, columns, constraints, and other objects. To retrieve a list of tables, the correct view isINFORMATION_SCHEMA.TABLES, which returns:

Table name

Schema name

Table type (BASE TABLE, VIEW, MATERIALIZED VIEW)

Creation timestamp

Owner and retention properties

The query:

SELECT * FROM INFORMATION_SCHEMA.TABLES;

returns metadata for all tables in thecurrent databasecontext.

INFORMATION_SCHEMA.COLUMNS returns column-level metadata, not table listings.

PUBLIC.INFORMATION_SCHEMA is invalid—INFORMATION_SCHEMA is not inside PUBLIC schema.

PUBLIC.TABLES is not a system object unless created manually.

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TheLIMITclause is used to restrict the number of rows returned by a query. The correct syntax in Snowflake is:

SELECT * FROM employees LIMIT 10;

This retrieves the first 10 rows of the result set. LIMIT appears at the end of the SELECT statement. Snowflake follows a SQL syntax similar to MySQL/PostgreSQL regarding LIMIT usage.

Incorrect forms include:

Using LIMIT before SELECT

Embedding LIMIT inside WHERE

Reversing the order of SELECT and LIMIT

LIMIT is frequently used for sampling, record previewing, debugging, and exploratory analysis.