Administering Snowflake I Course Overview

Minimum Required Prerequisites for Administering Snowflake I Course:

• Basic understanding of database administration concepts
• Foundational knowledge of Snowflake platform and its functionalities

Target Audience for Administering Snowflake I

Administering Snowflake I: A comprehensive three-day course designed for database administrators to master Snowflake Data Cloud's security, performance tuning, and data management features.

Target Audience:

• Database Administrators
• Data Engineers
• Cloud Solutions Architects
• Data Warehousing Specialists
• IT Security Professionals
• Data Integration Specialists
• IT Managers overseeing Data Teams
• DevOps Engineers
• System Administrators transitioning to cloud environments
• Technical Consultants and Advisors in Data Management

Learning Objectives - What you will Learn in this Administering Snowflake I?

Introduction: The Administering Snowflake I course is designed to equip database administrators with comprehensive skills in managing Snowflake environments, focusing on security, performance tuning, and data loading. Over three days, participants will gain hands-on experience through lectures, labs, and discussions.

Learning Objectives and Outcomes:

• Understand and utilize various clients and interfaces, including SnowSQL.
• Gain proficiency in managing security aspects, such as access, authentication, and security integrations.
• Design and implement effective role hierarchies, including user and role management.
• Master user management with a focus on password policies and session management.
• Configure and manage Snowflake account structures and virtual warehouse scaling.
• Work with a variety of database objects like tables, views, and semi-structured data.
• Efficiently manage data ingestion processes, including bulk loading and error handling.
• Load and query semi-structured data and understand schema inference and evolution.
• Create, manage, and query tasks and streams within Snowflake.
• Enhance query performance by writing efficient queries and utilizing system functions.
• Implement robust data governance practices, including classification, tagging, and access history auditing.