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What is a primary function of a view in Snowflake?
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.
Which of the following file formats can be processed by the PARSE_DOCUMENT function?
PARSE_DOCUMENT extracts text and, depending on mode, layout information from supported document formats. The function currently supportsPDF,PPTX, andDOCXfiles. For PDFs, it can perform OCR to extract scanned text or use LAYOUT mode to detect tables and structured regions. For PPTX files, it extracts slide text and content. For DOCX files, the function captures text and applies layout analysis. XLSX files are not supported---Excel content requires different extraction methods. PARSE_DOCUMENT enables automated document intelligence workflows entirely inside Snowflake, eliminating the need for external OCR or parsing services.
What are Snowflake notebooks primarily used for?
Snowflake Notebooks provide an interactive environment where developers and analysts can combineSQL,Python, visualization libraries, and documentation. Use cases include exploratory analysis, ETL prototyping, data engineering workflows, machine learning model development, and dashboard creation using Streamlit components.
Notebooks allow mixing of SQL and Python cells with shared session state, enabling smooth transitions between Snowpark DataFrames, SQL queries, visual charts, and markdown explanations. They enhance reproducibility and collaboration, supporting versioning, parameterization, and seamless Snowflake compute integration.
Incorrect options:
Raw data is stored in Snowflake tables, not in notebooks.
User authentication is handled by the Cloud Services Layer.
Managing cloud storage is automatic and not a notebook responsibility.
Thus, Snowflake notebooks are an end-to-end development and analytics interface.
What type of mode available in PARSE_DOCUMENT function? (choose two)
PARSE_DOCUMENT supports two processing modes:OCRandLAYOUT. OCR mode performs Optical Character Recognition, extracting raw text from scanned documents, images within PDFs, or low-quality text-based documents. It is ideal for scenarios like contract ingestion, receipt processing, or older scanned documents. LAYOUT mode extracts structured layout elements---tables, paragraphs, lines, bounding boxes---preserving the original document's spatial organization. This enables downstream analytical tasks such as table reconstruction or semantic segmentation of document content. OMR (Optical Mark Recognition) is not a supported feature, and ''CONTENT'' is not a valid mode. By supporting OCR and LAYOUT modes, Snowflake Cortex provides robust document intelligence capabilities directly within the Snowflake environment.
What is the PRIMARY purpose of the use of the PARSE_DOCUMENT function in Snowflake?
The PARSE_DOCUMENT function is part of Snowflake Cortex AI and is designed specifically to extract text, layout information, and structured elements from unstructured documents, especially PDFs. It supports OCR-based extraction for scanned files and layout-aware extraction to preserve tables, headings, and format structure.
Its purpose is not PII detection; Snowflake does not provide built-in automatic PII identification via PARSE_DOCUMENT. It does not identify candidate data for directory tables and is unrelated to JSON parsing---Snowflake uses PARSE_JSON for JSON data.
PARSE_DOCUMENT is primarily used for workflows such as contract analysis, invoice extraction, document classification, compliance automation, and downstream AI enrichment.
What is a key characteristic of a Snowflake virtual warehouse?
A virtual warehouse is the compute engine of Snowflake. It provides CPU, memory, and temporary storage needed to execute SQL queries, data loading operations, and DML actions. Warehouses can be sized dynamically and suspended or resumed to optimize cost.
Warehouses donotstore data; Snowflake's storage is independent and centralized. Warehouses do not manage roles---access control is handled through Snowflake's RBAC system. Encryption is performed automatically by Snowflake's storage and cloud services, not by warehouses.
Thus, the correct characteristic is that virtual warehouses supply compute.
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What is the SHOW GRANTS SQL command primarily used for?
SHOW GRANTS lists privileges assigned to roles, users, objects, or shares. It is essential for permissions auditing and RBAC management.
SHOW USERS lists users, not privileges.
Warehouse usage is in ACCOUNT_USAGE views.
Load history is retrieved via COPY_HISTORY or LOAD_HISTORY.
Exam domains verified against: Official Snowflake SOL-C01 exam guide, last checked October 2026.
Understand Snowflake's core features including elastic storage and compute, and learn to navigate key user interfaces like Snowsight, Notebooks, and Worksheets. Work with the Snowflake object hierarchy including databases, schemas, tables, and views to organize and structure your data effectively.
Define and manage role-based access control including role hierarchies and privilege assignment. Use database objects, schemas, and the INFORMATION_SCHEMA to understand context and manage access, then transfer ownership as needed using basic SQL commands.
Sample question from this domain above: Q7
Manage both structured and semi-structured data using stages and the COPY INTO command. Design and manage virtual warehouses including sizing and scaling decisions, then use multiple methods to load and query data including Snowsight and INSERT statements.
Sample question from this domain above: Q6
Implement continuous data protection using Time Travel and cloning to recover and manage data versions. Enable data sharing through Snowflake Marketplace and Data Exchange to share datasets securely with internal teams or external partners.
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