Resources for Snowflake

High-level overview of Snowflake's unified platform — how it brings together data warehousing, data lakes, data engineering, data science, data sharing, and AI/ML into a single, governed experience.

Snowflake's annual user conference featuring keynotes, technical sessions, hands-on labs, product announcements, and networking with the global data community.

Free self-paced training paths, role-based learning journeys, Hands-On Essentials badges, and Level Up micro-courses.

Free Coursera courses created by Snowflake's developer advocates, including Intro to Snowflake, Data Engineering, Advanced Data Engineering, and Generative AI.

Foundational overview of Snowflake's three-layer architecture (storage, compute, cloud services), table types (Snowflake, Iceberg, Hybrid), and integrated workloads across data engineering, analytics, AI/ML, and applications.

Interactive hands-on tutorials, quickstarts, and reference architectures across data engineering, AI/ML, app development, and more.

Interactive in-browser walkthroughs for exploring Snowflake features and use cases. Pre-configured worksheets, notebooks, or Streamlit apps with sample data — typically completed in under five minutes.

A series of weekly challenges released every Friday to help you practice and develop your Snowflake skills, created by Snowflake users, for Snowflake users.

Proctored exams at Associate, Core, Advanced (Architect, Data Engineer, Data Scientist, Administrator, Data Analyst, Security Engineer), and Specialty (Gen AI, Snowpark, Native Apps) levels.

Live and on-demand webinars covering new features, best practices, and customer stories.

Complete product documentation — SQL reference, user guides, developer guides, tutorials, and release notes.

Developer hub for downloading the Snowflake CLI, Snowpark, SnowSQL, ODBC driver, and other client libraries.

REST API for submitting SQL statements, checking execution status, and canceling queries. Supports OAuth and key-pair authentication.

Manage Snowflake objects — tables, warehouses, tasks, roles, stages, and more — programmatically in Python without writing SQL.

Procedural SQL extension for writing stored procedures, UDFs, and anonymous blocks. Covers variables, loops, cursors, RESULTSETs, conditional logic, and exception handling.

Connectors and drivers for Python, JDBC, ODBC, Node.js, Go, .NET, and PHP PDO.

470+ open-source repos including schemachange, sf-samples, demo notebooks, and quickstart companion code.

A searchable collection of whitepapers, videos, blog posts, and more.

Explore the ecosystem of 3rd-party partners and technologies certified to integrate with Snowflake.

Product demos, Summit talks, workload deep-dives, and feature walkthroughs.

Short-form tutorials, live coding, and product tips from Snowflake developer advocates.

Interviews with data and engineering leaders on architecture, strategy, and real-world Snowflake use cases.

Q&A forums, how-to guides, and the Data Superhero recognition program.

Elite group of Snowflake experts recognized for educating the community through blogs, videos, talks, and forum contributions.

Community program recognizing active online advocates — forum contributors, social media posters, content creators, and user group participants.

Get the latest information from the official Snowflake Blog.

Best practices, tips & tricks from Snowflake experts and community. Submissions welcome!

Technical deep dives from Snowflake's engineering team covering system internals, architecture decisions, infrastructure at scale, and behind-the-scenes innovation.

Unified SQL editor in Snowsight with file-based organization, side-by-side results, inline Copilot, and Git integration. Replacing Worksheets as the default editor.

Create team workspaces with wiki-style collaboration. Organize files in a shared database and schema, publish drafts, resolve conflicts, and control access with role-based sharing.

Jupyter-like notebooks running directly in Snowflake with SQL, Python, and Markdown. Available in Warehouse Runtime or Container Runtime (with GPU support).

Enhanced notebook experience with full Jupyter compatibility, terminal access, file management, and a pre-built container runtime optimized for AI/ML with CPU and GPU support.

The modern, open-source CLI for developer-centric workloads. Manages Streamlit apps, Native Apps, Snowpark, SPCS, notebooks, and SQL execution. Replaces legacy SnowSQL.

Write and execute SQL directly in VS Code with autocomplete, syntax highlighting, and Snowpark Python debugging. Includes object explorer, query history, and Native App support.

AI coding agent for Snowflake development. Generates, explains, and optimizes SQL and Python while respecting your warehouse's schemas and governance policies.

Run OCI-compatible containerized applications, ML models, and custom services on Snowflake-managed compute pools with GPU support.

Build, distribute, and monetize applications through the Snowflake Marketplace. Supports Snowpark, Streamlit, and containerized components.

Managed PostgreSQL instances running on Snowflake for transactional and operational workloads. Fully compatible with existing Postgres tooling, ORMs, and SQL clients.

Streamline the development lifecycle with Git integration, declarative object management (CREATE OR ALTER), parameterized Jinja templates, and CI/CD automation via Snowflake CLI and GitHub Actions.

Clone remote Git repositories (GitHub, GitLab, Bitbucket, Azure DevOps, AWS CodeCommit) into Snowflake. Sync branches, tags, and commits, execute SQL files directly, and push changes from Workspaces, Notebooks, and Streamlit apps.

Instrument and monitor applications with OpenTelemetry-based logs, metrics, and traces collected in Snowflake event tables. Includes Snowsight visualizations, alerts, notifications, and third-party tool integration.

Manage Snowflake resources as infrastructure as code using the official Terraform provider. Automate provisioning of databases, warehouses, roles, and other objects.

Automated code conversion tool that translates SQL from legacy platforms (Oracle, SQL Server, Teradata, Redshift, BigQuery, Spark, and more) into Snowflake-compatible SQL to accelerate migrations.

Build and deploy Streamlit apps directly within Snowflake. Data never leaves the secure environment. Available in Warehouse Runtime or Container Runtime.

Get started guide, API reference, and more advanced features of the core library including caching, theming, and Streamlit Components.

Quick-reference card for every Streamlit command and widget.

Daily bite-sized lessons that walk you from zero to a working Streamlit app.

Daily coding challenges building AI-powered Streamlit apps with Snowflake Cortex AI. Progresses from basic LLM calls through chatbots and RAG to multimodal AI and agents.

Every folder is an independent Streamlit app containing code, setup scripts, and sample data.

Serverless, continuous data loading from files in cloud storage stages. Triggers automatically via cloud event notifications or on-demand through REST endpoints.

Low-latency, row-level ingestion directly into Snowflake tables — no staging files required. Supports SDK-based and REST API ingestion with sub-second data availability.

Managed data integration service built on Apache NiFi. Connect virtually any data source with visual drag-and-drop flow creation for structured and unstructured data.

Load and query JSON, Avro, Parquet, ORC, and XML using VARIANT, ARRAY, and OBJECT types. Supports automatic schema detection, hierarchical nesting, and direct SQL querying.

Access and process files (images, PDFs, audio, video) stored in stages. Provides scoped, file, and pre-signed URLs, directory tables, and the FILE data type.

Native GEOGRAPHY and GEOMETRY types with WKT, WKB, GeoJSON, and EWKT support. Includes 80+ geospatial functions for spatial relationships, measurements, transformations, and H3 indexing.

First-class Iceberg table support with Snowflake-managed or externally managed tables, catalog-linked databases, and cross-engine interoperability.

Row-based table type optimized for low-latency, high-concurrency transactional workloads. Enforces primary key, foreign key, and unique constraints with row-level locking.

Specialized tables and warehouses for sub-second query latency at high concurrency. Designed for real-time dashboards, data APIs, and serving precomputed results.

Managed Iceberg REST catalog service built on Apache Polaris. Provides centralized, secure read/write access to Iceberg tables across REST-compatible query engines.

Deploy, execute, and schedule dbt Core projects natively in Snowflake as versioned DBT PROJECT objects.

Declarative data pipelines that automatically keep results up-to-date. Define the target state in SQL and let Snowflake handle incremental refresh.

Schedule and orchestrate SQL and procedural logic with tasks. Capture change data with streams for incremental processing.

Build data pipelines, UDFs, and stored procedures in Python, Java, or Scala that run directly on Snowflake compute.

Run pandas code at scale on Snowflake with minimal rewrites. Hybrid execution automatically routes operations to local pandas or the Snowflake engine based on data size.

Run existing PySpark DataFrame and Spark SQL workloads directly on Snowflake compute without managing a Spark cluster.

Define curated business definitions with dimensions, facts, and metrics. Powers Cortex Analyst for consistent natural language querying.

Overview of Snowflake's AI capabilities including Cortex AI Functions, Cortex Analyst, Cortex Search, Cortex Agents, and Snowflake Intelligence.

Serverless AI functions that run directly in SQL: AI_COMPLETE, AI_EXTRACT, AI_CLASSIFY, AI_SENTIMENT, AI_SUMMARIZE, AI_TRANSLATE, AI_EMBED, AI_REDACT, AI_AGG, and more.

Access frontier LLMs (Claude, GPT, Llama, Mistral, DeepSeek) via OpenAI- and Anthropic-compatible REST endpoints. Use existing SDKs with streaming, tool use, and structured output — all within the Snowflake governance perimeter.

Extract text, data, layout elements, and images from documents. LAYOUT mode preserves tables, headers, and reading order as Markdown; OCR mode provides fast text extraction. Supports PDF, Word, and image files.

Extract structured information — entities, lists, and tables — from documents using natural language questions. Powered by arctic-extract with support for fine-tuning on custom document types.

Extract images from PDFs and Word documents using AI_PARSE_DOCUMENT. Powers multimodal RAG, image classification, knowledge bases, and compliance workflows.

Interactive Snowsight UI for exploring AI_EXTRACT and AI_PARSE_DOCUMENT. Upload documents, ask extraction questions, preview layout and OCR results, and copy code snippets.

Vector and hybrid search service for building RAG applications and searchable knowledge bases over unstructured data.

Natural language to SQL for business users. Ask questions in plain English and get answers from your structured data.

Natural language analytics for business users. Build "data agents" that answer questions and take actions across platforms. Customize the interface with your own logo and application name for a branded experience.

Build agentic AI workflows that orchestrate across structured and unstructured data sources using tools like Cortex Analyst and Cortex Search.

Programmatically create, update, describe, list, delete, and run Cortex Agent objects via REST endpoints. Configure tools, instructions, orchestration budgets, and model selection.

Embed Snowflake's conversational AI agents into Microsoft Teams and Microsoft 365 Copilot. Business users query data with natural language and get answers, tables, and charts without leaving their chat.

Expose Cortex Analyst, Cortex Search, Cortex Agents, SQL execution, and custom UDFs/procedures to external AI agents via the Model Context Protocol (MCP) standard.

Customize LLMs on your own data using parameter-efficient fine-tuning (PEFT). Supports Llama and Mistral model families with a fully managed, serverless workflow.

Evaluate and trace generative AI applications using LLM-as-a-judge metrics (accuracy, groundedness, relevance), side-by-side comparison, and step-level execution tracing.

End-to-end ML platform for feature engineering, model training, deployment, and monitoring — all on governed data with CPU and GPU compute.

Immutable, versioned snapshots of training data with native connectors for PyTorch, TensorFlow, and Snowpark ML.

Define, manage, and discover ML features with automatic incremental refresh from batch and streaming sources.

Run ML workloads on Snowflake compute pools from any environment (VS Code, PyCharm, Jupyter). Dispatch functions, files, or modules to Container Runtime with GPU support.

Track and compare model training runs — log parameters, metrics, and artifacts, then evaluate results side-by-side in Snowsight.

Automatically tune model hyperparameters using distributed search strategies. Run grid, random, or Bayesian optimization on Snowflake compute pools.

Scale model training across multiple nodes using PyTorch distributed primitives. Train large models on GPU clusters managed by Snowflake compute pools.

Train separate models in parallel across data partitions. Ideal for segmented forecasting, per-customer models, or group-level predictions.

Log, version, and serve ML models as first-class Snowflake objects. Supports scikit-learn, XGBoost, PyTorch, TensorFlow, Hugging Face, MLFlow, and custom models.

Monitor production model performance, data drift, and volume over time. Set alerts on thresholds and compute Shapley values for model explainability.

Trace end-to-end data flow from source tables through feature views, datasets, and models. Enables reproducibility, compliance, and debugging.

Unified governance and discovery layer for data, apps, and models. Provides metadata, lineage, sensitive data classification, and access controls.

Central guide to governance features: data quality monitoring (DMFs), column-level security (masking policies), row access policies, object tagging, tag-based masking, sensitive data classification, access history, and object dependencies.

Automatically detect and classify sensitive data like PII, financial identifiers, and health information. Apply system tags based on semantic and privacy categories.

Visualize upstream and downstream dependencies for tables, views, and columns. Trace data flow, understand impact, and explore object relationships in an interactive graph.

Extend lineage beyond Snowflake to include external sources and transformations. Ingest lineage from third-party tools via OpenLineage to see the full data flow.

Track which users and roles accessed specific data objects and when. Query the ACCESS_HISTORY view for auditing, compliance, and understanding data usage patterns.

Automatically generate AI-powered descriptions for tables and columns in Snowsight. Improve data discovery and understanding with natural language documentation.

Search across all Snowflake objects from Snowsight. Find tables, views, databases, warehouses, and more using keywords, filters, and natural language.

Network policies, network rules, private connectivity, session policies, SCIM provisioning, and role-based access control (RBAC).

Connect to Snowflake over private networks using AWS PrivateLink, Azure Private Link, or Google Cloud Private Service Connect. Keep traffic off the public internet.

Evaluate and monitor security risks in your account. Includes CIS benchmark scanners, threat intelligence, MFA enforcement checks, and anomalous access detection.

Overview of sharing options: listings (cross-region, monetizable, Marketplace-ready), direct shares, Data Exchanges, and Reader Accounts for non-Snowflake users.

Share data products securely within your organization via the Internal Marketplace. Providers publish curated listings for internal discovery, with access controlled by account targeting and RBAC.

Secure, isolated environments for privacy-preserving data collaboration. Combine and analyze data across organizations without exposing raw records.

Overview of Snowflake's compliance certifications and regulatory frameworks including HIPAA, SOC 2, PCI-DSS, FedRAMP, GDPR, and industry-specific standards.

Point-in-time snapshots of tables, schemas, or databases for disaster recovery, regulatory compliance (SEC 17a-4, FINRA, CFTC), and cyber resilience.

Replicate databases, shares, and account objects across regions and cloud providers. Enable failover groups for business continuity and disaster recovery.

Self-service portal to download Snowflake's security certifications and compliance reports — SOC 1/2, ISO 27001, FedRAMP, HITRUST, PCI-DSS, GxP, C5, IRAP, CJIS, TISAX, and more.

Unified architectural framework for building secure, resilient, and efficient systems on Snowflake. Evaluate architectures and implement scalable solutions across five pillars of best practice.

Best practices for protecting data and managing access — covering authentication, authorization, encryption, network policies, and governance frameworks.

Guidelines for running and monitoring workloads effectively — including automation, deployment strategies, observability, and continuous improvement processes.

Strategies for building resilient architectures — covering failover, disaster recovery, replication, data durability, and business continuity planning.

Techniques for optimizing query performance and resource utilization — including warehouse sizing, clustering keys, caching strategies, and workload tuning.

FinOps principles for managing Snowflake spend — covering budgeting, resource right-sizing, workload efficiency, chargeback models, and cost-aware architecture patterns.

End-to-end guide covering cost concepts, exploring costs in Snowsight, chargebacks, budgets, resource monitors, and optimization strategies.

Set monthly spending limits with budgets (serverless + warehouses) or resource monitors (warehouses only). Configure alerts and auto-suspend at custom thresholds.

Query 1 year of historical usage data — warehouse metering, query history, storage, logins, and more — from the shared SNOWFLAKE database.

Pre-built Snowsight dashboards and sample queries using ORGANIZATION_USAGE and ACCOUNT_USAGE views to analyze credit consumption across accounts.

Automate row-level data archival and expiration with policy-driven SQL expressions. Move aging rows to lower-cost storage tiers and expire them after a configurable retention period.

Weekly updates on new features, behavior changes, and deprecations.

Real-time and historical data on system performance.

Discover and access 2,700+ listings from 670+ providers, including datasets, APIs, Native Apps, and AI products across finance, healthcare, geospatial, and more.

Landing page for Snowflake's industry-specific solutions, use cases, and partner ecosystems.

Unified data platform for banking, insurance, capital markets, and payments. Supports risk analytics, fraud detection, regulatory compliance, and secure data collaboration.

Build an AI and data foundation grounded in industry standards (HL7/FHIR, OMOP, FAIR, GxP, TEFCA) on HIPAA-eligible infrastructure.

Unify point-of-sale, inventory, and customer data for demand planning, personalization, supply chain visibility, and omnichannel analytics.

Data infrastructure for SaaS, platform, and technology companies. Covers product analytics, usage-based billing, data monetization, and customer 360.

Break down data silos across publishers, advertisers, and adtech platforms. Covers audience segmentation, identity resolution, campaign measurement, and content optimization.

Connect supply chain, IoT, and operational data for demand forecasting, quality analytics, predictive maintenance, and smart factory initiatives.

Consolidate network, subscriber, and usage data for churn prediction, network optimization, 5G analytics, and personalized customer experiences.

FedRAMP-authorized platform for government and education. Supports citizen services, fraud detection, public health surveillance, and cross-agency data sharing.

Unify booking, loyalty, and operational data for revenue management, personalized guest experiences, and real-time demand forecasting.

Use Snowflake as a security data lake for detection and response, threat hunting, cloud security management, and compliance.

Build Customer 360 profiles, modernize CDPs, and maximize marketing ROI. Covers identity resolution, audience segmentation, campaign measurement, and privacy-safe data collaboration.

Unify financial data for improved reporting, forecasting, and payment integrity. Provides real-time insights across budgeting, planning, and revenue analytics.

Simplify IT operations, reduce infrastructure costs, and boost organizational agility. Consolidate data management, enhance security visibility, and accelerate productivity across the enterprise.