Snowflake Advanced Training
Skip to Scheduled Dates
Course Overview
This 3-day course covers advanced Data Movement, Performance, Security, Agile Development and Data Sharing design considerations and best practices in the Snowflake Cloud Data Platform. This advanced course will consist of lecture, demos, and labs.
Who Should Attend
- Data Analysts
- Data Engineers
- Data Scientists
- Database Architects
- Database Administrators
Course Objectives
- Evaluate Snowflake’s advanced architectural concepts.
- Design a bulk loading and load troubleshooting strategy.
- Leverage the power of semi-structured and unstructured data.
- Use advanced query constructs for data analysis.
- Use event tables to collect and analyze logging and trace information.
- Develop a methodology for performance tuning your Snowflake Data Cloud.
- Use data sharing for collaboration in the Snowflake Data Cloud.
Course Outline
1 - Date and Time Data
- Date and Time Data Types
- Work with Dates and Times
- Time Series Data and ASOF Joins
2 - Geospatial Data Types
- Geospatial Overview
- Geometry Data
- Geography Data
- Using Geospatial Functions
3 - Working with Unstructured Data
- Overview
- Concepts
- Workflow
4 - Event Tables
5 - External Tables
- Querying External Data Lakes
- Creating and Querying External Tables
- Partitioning External Tables
6 - Dynamic Tables
7 - Hybrid Tables
8 - Iceberg Tables
- Data Lakes and Iceberg Tables
- Iceberg Tables in Snowflake
9 - Working with Stages
10 - Schema Inference and Evolution
- Loading and Transforming Semi-structured Data
- Schema Inference
- Schema Evolution
11 - Fixing Load Problems
12 - Group By and Grouping Sets
13 - Subqueries and Common Table Expressions (CTEs)
14 - Window Functions
- Overview
- Cumulative Window Functions
- Sliding Window Functions
15 - Querying Hierarchical Data
16 - Universal Search and Snowflake Copilot
17 - Notifications and Alerts
- Configure and Manage Snowflake Alerts
- Configure and Manage Notifications
18 - Automatic Clustering
- What is Data Clustering?
- Micro-partition Pruning (Elimination)
- Evaluating Clustering
- Implement and Test Cluster Keys
19 - Search Optimization
20 - Query Acceleration
21 - Materialized Views
- Overview
- Materialized View Use Cases
22 - Data Sharing
- Data Access Options
- Direct Data Sharing Workflow
< Back to Course Search
Class times are listed Eastern time
This is a 3-day class
Class dates not listed.
Please contact us for available dates and times.