In this role specific course covers Snowflake key concepts, features, considerations, and best practices intended for key stakeholders who will be accessing, developing, querying datasets for analytic tasks and building data pipelines in Snowflake. These stakeholders often consist of database application developers or data engineers. This course will consist of lectures, demos, labs, and discussions.
Learning Objectives:
- Overview of Snowflake key features and architecture
- Learn to access Snowflake through multiple UI and application methods
- Load, unload data sets
- Develop application for Snowflake including using comprehensive ANSI standard SQL support
- Performance and cost optimization techniques using caching and high performing functions
- Use Snowflake capabilities to work effectively with semi-structured data in Snowflake
- Tune queries and performance using advanced techniques such as data clustering and materialized views
- Leveraging Snowflake SQL extensibility features such as time travel capabilities, user-defined functions and stored procedures
Course content
Snowflake Architecture and Overview
- Snowflake technical overview
- Review three-tiered architecture
- Cloud services
- Virtual warehouse
- Storage
Interfaces and Connectivity
- Using Snowflake web console, worksheet
- Using Snowflake command line, SnowSQL
- Overview of connectors and ecosystem for Snowflake
Developing for Snowflake
- Overview of programmatic interfaces for Snowflake
- A deeper look at a specific programming interface such as Python and Spark
- Stored procedures
- External functions
- User defined functions
Loading New Data Sets
- Ingesting new data into Snowflake tables
- Working with various SQL data types
- Ingestion Snowflake best practices
Data Pipelines
- Continuous data processing using tasks
- Continuous data ingestion using SnowPipe
- Continuous change processing using streams
- Streaming connectors, such as Kafka for continuous ingestion
Data Lakes
- External tables and data lakes
- Partitioning for effecient queries over external files
- Materialized views sourced from external tables
Pipeline Transformations and Querying Data
- Review best practices of writing effective queries
- Filtering data examples and best practices
- Walk through grouping, rollups, and sorting data and performance considerations
- Usage and pitfalls of joining data
- Using Snowflake’s high performing approximation and estimation functions
- CTEs and analytic functions
Query Caching Performance Features
- Result set cache
- Metadata cache
- Query data cache
- Best practices of using caching for performance and cost optimization
Performance monitoring and management of query and ETL workloads
- Query profiling
- Virtual warehouse (compute resource) management
- Optimizing and tuning workloads
- Monitoring functions and cost management
Using Data Clustering Optimization for Advanced Query Performance Tuning
- How to identify appropriate use cases
- Designing clustering keys
- Auto-clustering service
- DML considerations
- Materialized views
- Search optimization service
Test, QA, and Production and Agile Development
- Time travel queries in Snowflake
- Cloning data and environment in Snowflake
Working with Semi-Structured Data
- Data source formats
- Support of native data types
- SQL operations (grouping, sorting and more)
- Built-in functions for traversing, flattening, and nesting of semi-structured data
Snowflake Data Cloud
- Data sharing Overview
- Snowflake Data Exchange and Snowflake Data Marketplace
- Secure views and UDFs
To see the full course content Download now
Course Prerequisites
- Basic knowledge of SQL is required
Who can attend
- Data Analysts
- Data Engineers
- Data Scientists
- Database Architects
- Database Administrators
Number of Hours: 30hrs
Certification
Key features
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
FAQs
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- Mock Interviews
- Video Tutorials
- Materials
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- Materials
- Preparing for Certification
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