SOL-C01 Exam Dumps - SnowPro Associate: Platform Certification Exam

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.

The Snowflake Data Cloud allows organizations toseamlessly share, access, and collaborate on dataacross departments and external partners, without copying or moving data. Through secure data sharing, listings, and data clean rooms, Snowflake eliminates data silos and dramatically improves data collaboration.

It does not eliminate the need for governance—Snowflake enhances governance via RBAC, masking policies, and centralized controls. It does not provide access to underlying cloud infrastructure; Snowflake abstracts that. It is not an on-premises solution; Snowflake is fully cloud-native.

Thus, the primary benefit is unifying and securely sharing data across the ecosystem.

==================

Snowflake Notebooks support multiple cell types for development and documentation.Pythoncells allow users to perform data transformations, analysis, and Snowpark operations.SQLcells enable executing Snowflake SQL queries directly against tables and views.Markdowncells support formatted documentation within notebooks—useful for narrative explanations and commentary. The option “Markup” is not a supported cell type in Snowflake Notebooks. These three supported types allow users to blend analytics, code execution, and documentation in a unified environment.

=======================================

Snowflake supports several numeric data types, includingINTEGER(and its aliases INT, BIGINT, SMALLINT, TINYINT) andFLOAT(a floating-point type). INTEGER represents exact whole numbers, and FLOAT supports approximate numerical values with fractional components. BOOLEAN is a logical data type used for TRUE/FALSE values, not numeric. VARCHAR is a string data type, also not numeric. Thus, INTEGER and FLOAT are the correct numeric data types supported by Snowflake.

=======================================

Executing anINSERTcommand in a Snowflake worksheet requires three components to be explicitly selected:

Active Warehouse– Provides compute resources to process the query. Without an active warehouse, DML operations cannot execute.

Database– The table receiving the INSERT must reside in the active database context.

Schema– The targeted table must be within a selected schema.

All three define the fully qualified context for locating and writing to the correct object. Snowflake’s compute/storage separation ensures compute is only used when warehouses are active. Schema and database selection ensure correct namespace resolution.

====================================================

A single VARIANT value in Snowflake has a maximum size limit of16 MB(uncompressed). This limit applies to semi-structured data stored in VARIANT, such as JSON, XML, Avro, and Parquet objects.

This limit ensures efficient storage, query performance, and micro-partitioning. Exceeding the size results in load or processing errors. For ingestion, when loading large JSON files, it’s recommended to break them into multiple objects or use JSON Lines formatting.

Snowflake has introduced an optional behavior change bundle (2025_03), increasing the limit to128 MBfor accounts that enable it, but the standard default remains 16 MB.

Thus, under default behavior,16MBis the correct maximum value size.

====================================================

Snowflake’s architecture is built on three primary layers that separate and optimize storage, compute, and services. TheData Storagelayer stores all structured and semi-structured data in Snowflake’s optimized, compressed columnar format. Snowflake manages file organization, metadata, and optimizations automatically, ensuring efficient storage management. TheQuery Processinglayer is implemented through virtual warehouses that independently execute queries using MPP (massively parallel processing) compute clusters. These warehouses scale elastically based on workload requirements. TheCloud Serviceslayer manages metadata, authentication, access control, query optimization, and infrastructure orchestration. This separation allows independent scaling of compute and storage, optimizing performance while simplifying administration.

=======================================

As a fully managed cloud data platform, Snowflake is responsible for infrastructure provisioning, hardware, software installation, platform upgrades, scaling, and internal metadata management such as micro-partitions and statistics. Customers do not manage physical hardware or install Snowflake software.

Customers are responsible for their data and its lifecycle within Snowflake. This includes loading data into tables from internal and external sources, unloading data when required, organizing data structures (databases, schemas, tables), defining access controls, and managing how data is used, transformed, and governed. They design schemas and workloads but do not manage the underlying engine. Therefore, “Loading, unloading, and managing data” correctly describes the customer’s responsibility.

==================