Advanced Snowflake: Deep Dive Cloud Data Warehousing and Analytics

Course details

Snowflake offers a powerful set of features for cloud data warehousing and analytics—and knowing how to use them effectively can significantly improve how your team processes and governs data. In this course, data engineer Janani Ravi takes you on a deep dive into Snowflake, covering advanced table structures, view types, continuous data pipelines, and semistructured data handling. Along the way, discover practical strategies to optimize query performance, manage user privileges, and implement access controls to create a more robust data governance framework. By the end of this course, you’ll be prepared to apply advanced Snowflake capabilities to large-scale data processing and analytics.

Concepts

Introduction

A quick overview of Snowflake
Snowflake architecture
Snowflake Edition platform and free trial setup
Quick overview of Snowsight
View query summaries

Table Structures and Types of Tables

Table structures in Snowflake
Data storage in Snowflake
Permanent, transient, and temporary tables
Permanent tables
Temporary tables
Transient tables
Cloning tables and data lineage
Specialized tables in Snowflake
Hybrid tables
External, Iceberg, and interactive tables
Time travel data retention and retention period
Query historical data using query ID and timestamps
Drop and undrop tables and disable time travel

Types of Views

Views in Snowflake
Create and query views
Create complex views involving joins
Create and query materialized views
Create and query secure views
Create and query recursive views

Performance and Optimization

Caching
Using the query results cache
Warehouse sizing
Configure warehouse sizing to improve performance
Query acceleration service
Configure query acceleration service
Clustering
Set up base table for query optimization comparisons
Create a clustered table
Execute point lookup and range queries on clustered tables
Search optimization
Enable search optimization
Execute point lookup queries on search optimized tables
Run substring queries on search optimized tables

Continuous Data Pipelines

Continuous data pipelines - Dynamic tables
Continuous data pipelines - Tasks and streams
Create and configure a dynamic table
Automated refresh of dynamic tables

Access and Query Semistructured Data

Create a stage to upload data
Load and query Parquet data
Load and query JSON data
Query and flatten arrays

Users and Privileges

Access control, users, and roles
Create users
View grants
Create roles and grant privileges

Conclusion

Summary and next steps