Data Engineering, Serverless ETL & BI on Amazon Cloud

🌟 Master Data Engineering on AWS Cloud with Serverless ETL & BI 🌟

Course Overview:

Embark on a transformative journey into the world of data engineering, where you'll learn to harness the power of Amazon Web Services (AWS) for setting up robust and scalable data warehouses, ETL processes, and BI infrastructures. This course is crafted to demystify the AWS ecosystem and empower Data Scientists, Analysts, and Business Analysts with the technical prowess required for efficient data handling.

What You'll Learn:

End-to-End Data Engineering Project Lifecycle:

• Setting up a Data Warehouse in AWS Redshift: Dive into creating a data warehouse from the ground up.
• Basic Data Warehousing Concepts: Grasp the fundamental principles that underpin effective data warehousing.
• Serverless AWS Glue Jobs: Master writing ETL and batch processing jobs using pyspark and python shell.
• AWS Athena for Ad-hoc Analysis: Discover how to leverage Athena for interactive querying, including insights on when to use it effectively.
• AWS Data Pipeline for Incremental Data Syncing: Learn to automate data synchronization using AWS Data Pipeline.
• Lambda Functions for ETL/Data Syncing Processes: Automate your ETL processes and data syncing with Lambda functions.
• QuickSight Setup, Analyses, and Dashboards: Develop your own QuickSight dashboards and gain insights from your data.

Prerequisites:

• Python/SQL: A solid foundation in Python and SQL is crucial.
• PySpark Knowledge: Basic familiarity with writing pyspark scripts.
• Will to Learn: A proactive attitude and a commitment to learning and succeeding.
• Active AWS Account: An active AWS account to work with the services (utilizing the free tier).

Important Notes:

• Free Tier Utilization: The course leverages AWS's free tier for Redshift and RDS, so there will be no additional charges unless usage exceeds free tier limits.
• AWS UI: This course focuses on the AWS UI for setting up clusters and tasks, requiring no bash scripting knowledge. It is designed to be compatible with any operating system.
• Coding Intensity: The course is not overwhelmingly coding-intensive; it involves 35% coding with a strong emphasis on execution, understanding, and component chaining.

Tips for Success:

• Watch Videos at 1.2X Speed: Maximize your learning efficiency by watching videos sped up.
• Research & Compare Tools: Each time you learn about a new tool or feature, take the initiative to research and compare it with similar offerings like Redshift/Athena vs Snowflake or BigQuery, QuickSight vs PowerBI vs Microstrategy. This will broaden your understanding and make you more versatile.

Enroll now and unlock the full potential of data warehousing, ETL, and BI on AWS Cloud! 🚀

This course is designed to ensure that by the end of it, you'll be confident in setting up, managing, and analyzing your data with serverless technologies on AWS. Don't miss this opportunity to elevate your skills and stay ahead in the ever-evolving field of data engineering. 📊✨