Managing Snowflake¶
These topics describes the tasks associated with using Snowflake.
Virtual warehouses — Key concepts and tasks for creating and using virtual warehouses to execute queries and perform DML operations, such as loading and unloading data:
Databases, Tables & Views — Key concepts and tasks related to understanding and working with Snowflake databases and tables:
Query Data in Snowflake — Key concepts and tasks for executing queries in Snowflake:
Date & time data types — Reference information and examples for working with dates, times and timestamps, and time zones in Snowflake:
Introduction to Loading Semi-structured Data — Key concepts and tasks for working with JSON and other types of semi-structured data:
Introduction to unstructured data — Key concepts and tasks for working with unstructured data:
String & binary data types — Reference information and examples for working with binary data in Snowflake:
Snowflake Time Travel & Fail-safe — Key concepts and tasks for understanding how Snowflake maintains access to deleted and modified data, and also how Snowflake enables data recovery in the event of loss:
Introduction to Streams and Tasks — Key concepts and tasks for transforming and optimizing loaded data for analysis:
Introduction to business continuity & disaster recovery — Key concepts and tasks for replicating and failing over objects across multiple Snowflake accounts, as well as redirecting client connections, for business continuity and disaster recovery:
Sample Data Sets — Key concepts and tasks for using the sample data sets provided with Snowflake: