- Basic knowledge of Databases
Audience
- Data analysts
Snowflake is a cloud-based data platform and data warehouse solution designed for the storage, processing, and analysis of large volumes of data.
This instructor-led, live training (online or onsite) is aimed at beginner-level data analysts who wish to utilize Snowflake effectively as they transition to the new environment.
By the end of this training, participants will be able to:
- Use the Snowflake web interface, SnowSQL, and other tools for data management.
- Configure roles, permissions, and data access controls to ensure data security.
- Use Snowflake's data sharing capabilities to collaborate and share data securely across accounts and organizations.
- Develop a basic migration plan, identify potential challenges, and validate data migration processes.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Introduction to Snowflake
- Overview of Snowflake's cloud data platform
- Key benefits and features
- Comparing Snowflake with traditional data warehousing solutions
Snowflake Architecture
- Multi-cluster shared data architecture
- Separation of storage and compute
- Data storage, compute resources, and cloud services
Getting Started with the Snowflake Environment
- Navigating the Snowflake interface
- Introduction to Snowflake Editions
- Setting up your first Snowflake account
Data Loading and Unloading
- Supported file formats and methods
- Using the Snowflake Web Interface, SnowSQL, and third-party tools
- Loading structured and semi-structured data
- Unloading data to external storage
Understanding Snowflake SQL
- Differences and similarities with traditional SQL
- Querying data in Snowflake
- Working with joins, subqueries, and common table expressions (CTEs)
- Overview of Time Travel and data versioning
Snowflake Security and User Management
- Managing roles and permissions
- Securing data with policies and access controls
- Integrating with Identity Providers (IdPs)
Performance Tuning and Query Optimization
- Best practices for efficient querying
- Using query profiling tools
- Auto-scaling and clustering considerations
Data Sharing and Collaboration
- Using Snowflake Data Sharing to share data securely
- Setting up data sharing and accessing shared data
- Working with Snowflake Marketplace
Working with Semi-Structured Data
- Handling JSON, Avro, Parquet, and ORC formats
- Using Snowflake's VARIANT data type
- Querying and transforming semi-structured data
Data Warehousing and Data Modeling Best Practices
- Building data models in Snowflake
- Best practices for schema design and data partitioning
- Using materialized views and clustering keys
Setting up a Migration Plan
- Creating a basic migration plan to Snowflake
- Identifying potential challenges and solutions
- Testing and validating data migration
Summary and Next Steps