Snowpro Training

• Understand the architecture and unique features of Snowflake, the leading cloud-based data warehousing platform.
• Load and transform data using various methods and handle different data formats in Snowflake.
• Perform complex data queries using Snowflake SQL.
• Leverage Snowflake's data sharing capabilities for secure and easy access to shared data.
• Solve real-world problems using Snowflake through hands-on projects, demonstrating practical competence.
• Prepare for the SnowPro certification, validating their proficiency in using Snowflake.

• Recorded Videos After Training
• Digital Learning Material
• Course Completion Certificate
• 24x7 After Training Support

• IT Professionals
• Software Engineers
• Project Managers and Team Leaders
• Aspiring Data Professionals
• Snowflake Enthusiasts

• Understanding of Database Concepts: Basic knowledge of relational databases, SQL, and data warehousing concepts would be beneficial.
• Experience with Data Analysis: Some experience with data analysis, such as data extraction, transformation, and loading (ETL) processes, will enhance your learning experience.
• Familiarity with Cloud Computing: While not mandatory, understanding the basics of cloud computing platforms, particularly in terms of data storage and management, can be advantageous.
• Computer Skills: The ability to install software and set up a working environment on your computer is essential.
• Learning Mindset: Above all, you should have a willingness to learn new concepts, a proactive attitude for solving problems, and an eagerness to take on hands-on projects.

• Multisoft Systems provides a globally recognized training certificate after successful completion of SnowPro Training Course.

Account and Security (10 – 15%)

• Snowflake accounts and usage monitoring
• Security principles and policies like Multi-factor Authentication (MFA), Single Sign-On (SSO), data encryption, access control, and federated authentication
• Snowflake roles and entities including Role Hierarchy and Privilege Inheritance
• Snowflake Data Governance and security features like data masking and External Tokenization

Virtual Warehouses (15 – 20%)

• Learning about compute principles like credit usage, billing, concurrency, and caching
• Understanding virtual warehouse best practices for monitoring, management, and scaling

Data Movement (11 – 20%)

• Differentiation between data loading commands like COPY, INSERT, PUT, GET, and VALIDATE
• Defining bulk vs. continuous data loading methods like COPY and Snowpipe
• Data loading best practices for file size and folders
• Best practices and formats for unloading data from Snowflake to local storage or cloud storage
• Manipulating semi-structured data

Performance Management (5 – 10%)

• Best practices for clustering, materialized views, and search optimization on storage
• Best practices for query performance and analysis, query profiles, query history, SQL optimization, and caching on virtual warehouses

Snowflake Overview and Architecture (25 – 30%)

• Snowflake’s cloud data platform 
• Data marketplace and web interface (UI)
• Snowflake’s data sharing functionalities
• Snowflake versus legacy warehouse solutions
• Features of different Snowflake editions
• Snowflake’s Partner Ecosystem including cloud partners and connectors  
• Snowflake’s three distinct layers storage layer, compute layer, and cloud services layer 
• Snowflake’s catalog and objects including database, schema, tables types, view types, data types, and external functions

Storage and Protection (10 – 15%)

• Snowflake’s storage concepts like micro partitions, metadata types, clustering, data storage, stage types, file formats, and storage monitoring
• Continuous data protection including time travel, fail safe, data encryption, and cloning