Advanced Snowflake Course Syllabus

Snowflake Course Outline

The Snowflake platform is a cloud-based data warehousing solution that offers a unique architecture, enabling high performance, scalability, and concurrency. Whether you're a data analyst, database administrator, or IT professional, mastering Snowflake can significantly enhance your career prospects. The Snowflake course syllabus is designed to cover all essential aspects of the platform, ensuring that learners gain a thorough understanding of its functionalities and applications.

Snowflake training covers cloud data warehousing, architecture, and features. It includes data loading, querying, performance optimization, security, and integration with various tools. The course blends theoretical concepts with practical exercises, preparing participants for efficient Snowflake implementation and management.

1. Introduction
2. Roles
3. Snowflake Pricing
4. Resource Monitor – Track Compute Consumption
5. Micro-Partitioning in Snowflake
6. Clustering in Snowflake
7. Query History & Caching
8. Load Data from AWS – CSV / JASON / PARQUET
9. Load Data from Azure
10. Snow pipe – Continuous Data Ingestion Service 
11. Different Type of Tables
12. Time Travel – Work with History of Objects & Fail Safe
13. Task in Snowflake – Scheduling Service
14. Snowflake Stream – Change Data Capture (CDC)
15. Zero-Copy Cloning
16. Snowflake SQL – DDL
17. Snowflake SQL – DML & DQL
18. Snowflake SQL – Sub Queries & Case Statement
19. Snowflake SQL – SET Operators
20. Snowflake SQL – Working with ROW NUMBER
21. Snowflake SQL – Functions & Transactions
22. Procedures
23. Data Masking
24. Row level security
25. Shares
26. ALL TYPE OF VIEW
27. User defined function
28. External Tables
29. Working with power BI
30. Migration project – On-Premises to Snowflake
31. Mock Interview sessions

Snowflake Differentiating Real-time Content

1. Data Warehousing Basics/Recap

• OLTP VS OLAP

2. Key Cloud Computing Concepts

• Cloud Introduction
• On-Premises vs IaaS vs PaaS vs Saas

3. Snowflake Introduction

• Getting started with snowflake
• Cloud providers that Snowflake supports
• Snowflake editions
• Connecting to Snowflake

4. Snowflake Architecture

• Shared Disk & Shared Nothing Architectures
• Deep dive on Layers in snowflake architecture
• Centralized Storage
• Compute
• Cloud Services  and Cloud Agnostic Layer

5. Building a Snowflake Virtual Warehouse

• Creating a warehouse
• Deep dive on properties of warehouses
• Warehouse Sizes
• Multi-Cluster Warehouses
• Compute Cost optimization
• Scale Up vs Scale-Out
• Multi-warehouse modes
• Maximized 
• Auto-Scale 
• Scaling policy
• Standard policy 
• Economy policy
• Auto Suspend & Auto Resume
• Real challenges in Warehouse perspective

6. SNOWFLAKE OBJECTS

• Account Level
• Warehouse
• Database
• Schema level
• Tables
• Views
• Stages
• File Formats
• Sequences 
• Pipes 
• Stored Procedures
• User Defined Functions

7. Tables & Views

• Deep dive into Permanent, Transient, Temporary, and External tables
• Managing external tables and stages
• Views
• Regular, Materialized, secure views

8. Storage features

• Time Travel (UNDROP)
• Fail-Safe
• Zero-Copy Cloning (Deep dive on how it actually works)

9. Snowflake Administration

• Roles in Snowflake
• ACCESS MANAGEMENT KEY CONCEPTS
• Discretionary Access Control (DAC) 
• Role-Based Access Control (RBAC)
• RBAC vs DAC
• Default Roles in Snowflake.
• ROLES ENCAPSULATION
• ROLES COMMANDS
• Network policies in Snowflake

10. PRICING - COSTS IN SNOWFLAKE

• Storage Costs
• Compute Costs
• Cloud Services Costs and Data Transfer Costs
• Capacity options (in terms of buying snowflake service)
• On-Demand 
• Pre-paid

11. Data Organization in Snowflake storage

• SNOWFLAKE MICRO-PARTITIONS
• SNOWFLAKE PRUNING PROCESS
• Clustering
• DATA CLUSTERING
• CLUSTERING DEPTH
• CLUSTER KEYS
• RECLUSTERING

12. AWS for Snowflake

13. Stages

• External Stages
• Internal stages
• User stage
• Table stage
• Named internal stage

14. Storage Integration

15. File Formats

• Structured Data
• Semi-structured Data

16. Sequences

• Creating sequences
• Difference in the behavior of sequences with respect to RDBMS

17. Getting Started with SnowSQL

• Data Loading
• Staging the data
• How to access/load data from cloud storage (AWS S3, Azure Blob and Google cloud storage)
• BULK LOADà
• Deep dive into COPY INTO command with all options and their project usage scenarios
• Real Issues that we encounter in copy into implementation with solution
• Error handling in data loads
• Bulk Data Loading Recommendations
• File Preparation (Sizing, splitting)
• CONTINUOUS LOADà
• Snowpipe
• Snowpipe configuration
• Integrating with cloud storage
• Real issues with snowpipe and how we overcome them
• Error handling and monitoring
• Data unloading from snowflake
• Bring data into snowflake stage and download

18. Working with Semi-structured Data

19. Cache

• METADATA CACHE
• QUERY RESULT CACHE
• WAREHOUSE CACHE
• Deep dive on all caches

20. Optimize Snowflake Query Performance

21. Stored Procedures and Functions

22. Tasks

• TREE OF TASKS
• TASK HISTORY
• Limitations of tasks

23. Transactions in Snowflake

• Nested transactions
• Issues encountered with transactions

24. Streams

• Types of Streams
• Practical examples that covers all stream use cases

25. Building Data Pipelines in Snowflake

• Incremental/Delta and Historical data load implementation in real world (SCD scenarios)
• Error handling in data pipelines

26. Generic  stored procedure frame work for Data loads
27. Migration to Snowflake

28. Advanced SQL Techniques

29. Snowflake Connector for python

30. Secure Data Sharing

• PRODUCERS
• CONSUMERS
• Full Account 
• Reader Account
• INBOUND & OUTBOUND SHARES

31. Setting Up Load Monitoring

• Best Practices for Load Monitoring

32. Resource Monitors

• Resource Monitors Assignment
• Resource Monitors Parameters

33. Snowflake Security

• SNOWFLAKE COMPLIANCE
• COLUMN LEVEL SECURITY
• Dynamic Data Masking
• External Tokenization

34. Overview on End to End Snowflake Project implementation

35. SNOWFLAKE DATA MARKETPLACE

• Standard Data Listing
• Personalized Data Listing (Premium)

36. SNOWFLAKE ECOSYSTEM

• Partner Connect
• Technology partners
• Solution partners
• Partner classification

37. Matillion or Informatica Cloud (IICS) for Snowflake

38. Snowpark Overview

39. Expected features in future/preview features

Hands-On Experience and Real-world Applications

One of the most valuable aspects of the Snowflake course syllabus is the focus on practical, hands-on experience. Learners are typically required to complete projects and assignments that simulate real-world scenarios, enabling them to apply what they've learned in a controlled environment. This practical approach helps to solidify the theoretical concepts covered in the course and ensures that learners are well-prepared for the challenges they will face in the workplace.

Certification and Beyond

Upon completing the Snowflake course content, learners are usually well-prepared to pursue Snowflake certification. Certification not only validates your knowledge and skills but also enhances your employability in the competitive job market. The course often includes reviewing potential exam questions and scenarios, ensuring you are fully equipped to pass the certification exam.

The Snowflake course curriculum is comprehensive and designed to equip you with all the necessary skills to excel in data warehousing and cloud computing. By covering both foundational and advanced topics, the syllabus ensures that learners understand Snowflake's capabilities deeply. Whether you're looking to advance your career or switch to a role that leverages the power of Snowflake, this course is an excellent investment in your future.