Snowflake SnowPro Associate Platform Quick Facts (2025)

Exam Domain Breakdown

Domain 1: Interacting with Snowflake and the Architecture (35% of the exam)

1.1 Outline key features and benefits of the Snowflake AI Data Cloud.

• Elastic storage
• Elastic compute
• Snowflake layers

1.1 summary: This section focuses on the essential advantages of the Snowflake AI Data Cloud. You will explore how elastic storage allows you to scale data usage without limitations, and how elastic compute ensures performance flexibility for a wide variety of workloads. Understanding these concepts highlights how Snowflake balances power with efficiency across diverse use cases.

Additionally, this part emphasizes how Snowflake’s layered architecture supports performance, scalability, and ease of use. By connecting these technical capabilities with their business value, you will see how Snowflake enables organizations to deliver reliable and seamless data-driven outcomes across industries.

1.2 Outline the key Snowflake user interfaces.

• Snowsight
• Snowflake Notebooks
• Worksheets with Python
• Worksheets with SQL

1.2 summary: This section covers the primary ways to interact with Snowflake. You will learn about Snowsight, the modern and intuitive graphical interface for queries, dashboards, and support tools. It also introduces Snowflake Notebooks, a flexible environment that allows you to combine SQL and Python interactively for richer analysis.

Key details include how notebooks and worksheets work together to support different styles of workflow, and how these variations serve both analysts and developers. Together, these interfaces demonstrate Snowflake’s adaptability for a broad spectrum of professionals seeking to derive insights and build solutions.

1.3 Describe how to use the Snowsight user interface.

1.3 summary: This section highlights how Snowsight is more than just a query editor. You will learn how it provides visualizations, query history, and monitoring tools to simplify day-to-day work. Through Snowsight, Snowflake makes activities such as data exploration and resource management accessible to technical and non-technical users alike.

Beyond its basic functionality, Snowsight empowers users with the ability to collaborate by sharing queries, examining performance metrics, and leveraging built-in data visualizations. The intuitive design of Snowsight reinforces Snowflake’s emphasis on accessibility and enhances productivity for teams of all sizes.

1.4 Work with Snowflake Notebooks.

• Notebook sessions
• Run code with SQL
• Run code with Python
• Cell execution status
• Visualize data using Streamlit
• Python variable substitution

1.4 summary: This section walks through the interactive workflow experience made possible with Snowflake Notebooks. You will learn how to manage notebook sessions, run SQL and Python side by side, and visualize results within the same interface. This unification of languages and visualization strengthens collaboration and speeds up data experimentation.

Additionally, the section examines helpful notebook capabilities such as cell execution status, variable substitution, and Streamlit visualizations. By combining multiple tools into a single workflow, Snowflake Notebooks helps make data science and data analysis seamless and more efficient.

1.5 Describe Snowflake objects and how they fit into the Snowflake hierarchy.

• Databases
• Schemas
• Tables
• Views
• Data types
• Data loading
• Query history
• Object browsers such as creating databases, schemas, and stages

1.5 summary: This section introduces the hierarchy and structure of Snowflake objects. You will learn how core objects such as databases, schemas, tables, and views interconnect in Snowflake’s organized framework. An understanding of object hierarchy is fundamental for ensuring consistency, security, and effective use of Snowflake’s resources.

In addition, this section touches on important operational features including data types, query history, and object browsers for creating and managing objects. Collectively, these concepts provide the foundation for all workflows inside Snowflake.

Domain 2: Identity and Data Access Management (15% of the exam)

2.1 Define the roles that are used in Snowflake.

• Role-Based Access Control (RBAC) and role hierarchy
• Role types
• Privileges
• Object access by role

2.1 summary: This section emphasizes how Snowflake secures data through role-based access. You will examine RBAC concepts, including role hierarchy and the assignment of privileges. Learning these core ideas helps ensure the right individuals have access to the right resources while maintaining organizational security.

Beyond technical access, the section explains how object access is managed by roles, and how different role types align with business needs. This lays the groundwork for building secure collaboration environments in Snowflake.

2.2 Create a database, explore data, configure parameters, and transfer ownership.

• Use of database objects and INFORMATION_SCHEMA
• Use of the PUBLIC schema
• Understanding context
• Transfer ownership
• Create and drop schemas
• Basic SQL commands such as EXCLUDE, SELECT *, and LIMIT

2.2 summary: This section focuses on applying access and identity concepts while working with Snowflake databases. You will learn how to use schemas, parameters, and SQL commands to explore and manage data. Key concepts include ensuring context is properly set while working within and across databases.

The ability to transfer ownership and configure parameters plays a central role here, enabling teams to maintain clear authorization while still providing flexibility. Mastering these steps helps professionals build reliable governance processes within Snowflake.

Domain 3: Data Loading and Virtual Warehouses (40% of the exam)

3.1 Describe considerations when working with structured and semi-structured data.

• Stages
• Loading and querying structured data
• Loading and querying semi-structured data
• Commands such as COPY INTO, INSERT, and LIST

3.1 summary: This section explores Snowflake’s ability to handle both structured and semi-structured data without requiring different systems or tools. You will learn how stages act as essential areas for organizing and loading files before integrating them into Snowflake.

Beyond the mechanics of loading, the section looks at querying data effectively and the commands that make this possible. Understanding these capabilities ensures that Snowflake users can leverage data stored in diverse forms for powerful analytics.

3.2 Explain virtual warehouses.

• Standard warehouses compared to multi-clustered warehouses
• Warehouse sizing
• Scaling in or out
• Scaling up or down

3.2 summary: This section is all about compute resources in Snowflake. You will learn how virtual warehouses provide the processing power behind queries, loads, and transformations. A key concept here is the distinction between standard warehouses and multi-cluster warehouses for scaling performance.

Warehouse sizing, scaling in or out, and scaling up or down are discussed in detail, showing how Snowflake offers flexibility. This ensures workloads run smoothly, cost-effectively, and with the required level of performance.

3.3 Create tables in Snowflake and load data into the tables.

• Using Snowsight to identify tables
• Viewing table definitions
• Previewing table data
• Inserting records
• Loading data with Snowsight
• Using COPY INTO table statements with file format options

3.3 summary: This section demonstrates how to move data from files into structured Snowflake tables. You will work with Snowsight to explore tables, review definitions, and preview data, then practice inserting and loading records.

By combining tools like COPY INTO with Snowsight’s visual approach, Snowflake ensures flexibility for both technical and non-technical professionals. These practices provide the foundation for building trusted datasets ready for analysis.

3.4 Explain how to work with unstructured data.

• Directory tables setup
• Using SELECT statements with directory tables
• Pre-signed URLs with function arguments

3.4 summary: This section extends the data loading and querying experience to unstructured content. You will learn how directory tables organize unstructured files, making them easy to query and work with. Using SELECT queries against directory tables becomes key for unlocking insights that reside in non-tabular formats.

Additionally, the use of pre-signed URLs ensures secure and efficient access to data while maintaining Snowflake’s focus on governance and compliance. Together, these practices make unstructured data a seamless part of analysis within Snowflake.

3.5 Explain how to use Snowflake Cortex LLM functions.

• PARSE_DOCUMENT function
• TRANSLATE function
• CLASSIFY_TEXT function
• COMPLETE function

3.5 summary: This section showcases innovative AI-powered features that integrate directly into the platform. You will work with Cortex LLM functions such as PARSE_DOCUMENT and TRANSLATE to enrich workflows with intelligent language processing.

In addition, CLASSIFY_TEXT and COMPLETE demonstrate Snowflake’s ability to support advanced natural language scenarios right inside SQL. By learning these functions, you can bring machine learning and language intelligence into your everyday data practices.

Domain 4: Data Protection and Data Sharing (10% of the exam)

4.1 Outline continuous data protection with Snowflake.

• Time Travel
• Cloning

4.1 summary: This section explains how Snowflake maintains continuous protection of your data. You will learn how Time Travel enables recovery of historical data, and how cloning empowers instant duplication of data objects without additional storage costs.

Together, these features provide resilience, boost productivity, and create trust in the platform’s ability to safeguard information. They also pave the way for safer experimentation with datasets without compromising business continuity.

4.2 Define Snowflake data sharing capabilities.

• Snowflake Marketplace search listings
• Data Exchange using private data shares

4.2 summary: This section highlights how Snowflake enables easy and secure data collaboration. You will explore Snowflake Marketplace for discovering and sharing curated data listings with just a few clicks.

It also covers private data sharing through Data Exchange, ensuring that businesses can collaborate closely with partners while maintaining governance and trust. These capabilities represent one of Snowflake’s most transformative strengths in enabling the data economy.