Snowflake cloud database with ELT(Airflow+Python+Talend)

Overview

In our previous course Snowflake Masterclass [Real time demos+Best practices+Labs] we deep-dived and understood the fundamentals of snowflake, solved lot of assignments, and understood best practices to load data and unload data.

Syllabus

• Introduction to Snowflake and ELT
Overview of Snowflake's architecture
Introduction to ELT concepts
Setting up your Snowflake environment
• Data Loading with Snowflake
Data ingestion techniques
Best practices for data loading
Hands-on lab: Loading data into Snowflake
• Introduction to Apache Airflow
Understanding Airflow architecture and components
Setting up an Airflow environment
Defining and scheduling workflows
• Integrating Airflow with Snowflake
Writing and orchestrating DAGs for Snowflake
Monitoring and maintaining workflows
Hands-on lab: Creating an Airflow DAG for Snowflake pipeline
• Python for Data Processing
Python basics for ETL/ELT
Using Python libraries (Pandas, NumPy) for data transformation
Hands-on lab: Python data transformation scripts
• Talend for Data Transformation
Introduction to Talend Studio
Designing data transformation workflows with Talend
Best practices for using Talend with Snowflake
• Building an End-to-End ELT Pipeline
Integrating Airflow, Python, and Talend for ELT
Orchestrating complex workflows
Hands-on lab: Building an end-to-end ELT pipeline
• Best Practices and Optimization
Performance tuning for ELT processes
Security considerations with Snowflake
Troubleshooting common ELT issues
• Capstone Project
Designing and implementing a complete ELT solution
Presentations and peer reviews
• Wrap-up and Next Steps
Course summary and key takeaways
Further learning resources and certifications

Taught by

Pradeep H C

Subjects

Business