Free Snowflake SOL-C01 Practice Exam with Questions & Answers | Set: 5

The Database Storage Layer is responsible for persistently storing all customer data in Snowflake. This layer automatically manages micro-partitioning, compression, and metadata. Data is stored in optimized, columnar formats inside cloud object storage (AWS S3, Azure Blob Storage, or GCP Storage). Users cannot manipulate physical storage directly; access is only through SQL operations. Other layers serve different purposes: Cloud Services manages metadata and orchestration, Query Processing Layer executes workloads, and Virtual Warehouses provide compute but do not store data.

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A view in Snowflake represents avirtual tablewhose contents are defined by a stored SQL query. Views allow users to encapsulate transformation logic, simplify complex joins, enforce column-level security, and provide curated datasets for downstream consumers.

Views donotstore data themselves; the underlying tables store the data, and Snowflake executes the view’s query each time the view is referenced. This makes views ideal for abstraction layers, semantic modeling, and separating compute costs across user groups.

Incorrect options:

Snowflake views do not store raw data.

Views have no role in authentication or network configuration.

Views help streamline business logic and control data access efficiently.

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Snowflake’s object hierarchy begins with theaccount, which contains one or moredatabases. Each database can contain multipleschemas, and each schema contains objects such astables,views,stages, and functions. The schema is a logical boundary for grouping related database objects. A schema cannot contain databases, and tables cannot contain schemas. Instead, tables and views are contained within schemas. Therefore, the two correct hierarchical relationships are that a database can contain multiple schemas, and a schema can contain multiple tables and views.

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The COMPLETE function enables natural language generation within Snowflake Cortex. It accepts a prompt and produces a text-based completion using an underlying large language model (LLM). COMPLETE can generate single-turn or multi-turn responses, depending on how the prompt is structured. It is used for tasks such as drafting summaries, generating recommendations, writing structured output such as JSON, or extending existing text. It is not a classification tool—that role is served by CLASSIFY_TEXT—and it does not perform linguistic translation (TRANSLATE) or document extraction (PARSE_DOCUMENT). COMPLETE allows developers and analysts to embed AI-driven generative capabilities directly within SQL pipelines or Snowpark processes, eliminating the need for external LLM services.

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Snowflake’s foundational security capability isalways-on end-to-end encryption, applied to all customer data both at rest and in transit. Snowflake encrypts data stored in micro-partitions using AES-256, and all network communication uses TLS encryption. Key management is automated through Snowflake’s hierarchical key model, providing additional rotation, rekeying, and defense-in-depth mechanisms.

While RBAC, masking policies, and network policies are crucial components of Snowflake security, encryption is the platform’s guaranteed, baseline, mandatory protection feature. It applies universally to all data, regardless of workload, role configuration, or user settings.

Option A: automated masking is optional and policy-driven, not a primary universal mechanism.

Option B: network perimeter defense exists but is not the platform’s core foundation.

Option C: RBAC controls access but does not protect data itself.

Thus, Snowflake’s primary and most universal security capability is end-to-end encryption.

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Snowflake’s multi-cluster shared data architecture enablesindependent scaling of compute and storage, meaning workloads can be sized differently without affecting stored data.

It also providesnear-unlimited concurrency, because Snowflake can automatically add compute clusters during peak loads.

Snowflake does not require manual infrastructure management and runs fully in the cloud—not on-premises. Multi-cloud support reduces vendor lock-in, not increases it.

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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 Query Processing Layer executes SQL statements using virtual warehouses and massively parallel processing. It handles query optimization, execution, and scaling. The Cloud Services Layer parses and plans queries but does not execute them. Storage persists data, and the Client Layer is external to Snowflake architecture.

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ThePARSE_JSON()function converts a valid JSON string into aVARIANTvalue. This allows Snowflake to store and query nested, hierarchical data using dot and bracket notation.

Example:

SELECT PARSE_JSON('{"name":"John","age":30}') AS data;

After parsing, fields can be accessed like:

data:name or data['age']

Incorrect options:

TO_JSON()converts VARIANT to a JSON string (opposite direction).

CONVERT_JSONandEXTRACT_JSONare not Snowflake functions.

PARSE_JSON is essential for dynamically loading, transforming, or analyzing JSON content from files, streams, or external applications.

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Snowflake Data Exchange is not enabled by default. Accounts must open a support request to Snowflake Support, which then activates the feature. It cannot be enabled via UI or SQL. After activation, administrators may create private exchanges and listings.

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