Snowflake

Course Overview

Throughout the course, there would be a mix of lectures, hands-on labs, and assignments to reinforce learning. Additionally, periodic assessments and quizzes would be conducted to gauge understanding and progress.

Course Curriculum

Week 1: Introduction to Snowflake

Overview of Snowflake: Understanding its architecture, key features, and advantages.
Setting up Snowflake: Creating an account, navigating the interface, and configuring basic settings.
Data Loading: Uploading data into Snowflake from various sources (CSV, JSON, etc.).
Data Warehousing Concepts: Understanding data warehousing principles and how Snowflake implements them.
Hands-on Lab: Loading and querying data in Snowflake.

Week 2: Data Modelling in Snowflake

Week 3: Advanced SQL in Snowflake

Week 4: Performance Tuning and Optimization

Week 5: Security and Compliance

Week 6: Advanced Topics and Best Practices

Snowflake

Course Overview

Course Curriculum

Week 1: Introduction to Snowflake

Overview of Snowflake: Understanding its architecture, key features, and advantages.

Setting up Snowflake: Creating an account, navigating the interface, and configuring basic settings.

Data Loading: Uploading data into Snowflake from various sources (CSV, JSON, etc.).

Data Warehousing Concepts: Understanding data warehousing principles and how Snowflake implements them.

Hands-on Lab: Loading and querying data in Snowflake.

Week 2: Data Modelling in Snowflake

Introduction to Data Modeling: Conceptual, logical, and physical data models.

Designing Tables: Creating tables in Snowflake, defining data types, and setting constraints.

Working with Schemas: Organizing tables within schemas, managing access control.

Relationships and Joins: Understanding relationships between tables and performing joins.

Hands-on Lab: Creating a data model in Snowflake.

Week 3: Advanced SQL in Snowflake

SQL Basics in Snowflake: Writing SELECT queries, filtering data, and sorting results.

Aggregate Functions: Using SUM, AVG, COUNT, and other aggregate functions.

Window Functions: Understanding window functions for advanced data analysis.

Subqueries and Common Table Expressions (CTEs): Writing complex queries.

Hands-on Lab: Advanced SQL queries in Snowflake.

Week 4: Performance Tuning and Optimization

Query Optimization: Understanding query execution plans and optimizing performance.

Indexes and Clustering Keys: Improving query performance with indexing.

Materialized Views: Accelerating query performance with materialized views.

Resource Management: Managing resources and optimizing concurrency.

Hands-on Lab: Performance tuning in Snowflake.

Week 5: Security and Compliance

Security Best Practices: Understanding roles, privileges, and access controls.

Data Encryption: Encrypting data in transit and at rest.

Regulatory Compliance: Ensuring compliance with industry standards (GDPR, HIPAA, etc.).

Auditing and Monitoring: Monitoring user activity and auditing data access.

Hands-on Lab: Implementing security measures in Snowflake.

Week 6: Advanced Topics and Best Practices

Semi-structured Data: Working with JSON and other semi-structured data formats.

Data Sharing: Sharing data securely between Snowflake accounts.

Time Travel and Data Versioning: Understanding data retention and recovering data.

Snowflake Ecosystem: Integrating Snowflake with other tools and platforms.

Capstone Project: Applying all learned concepts to solve a real-world problem.

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