ETL Fundamentals for Advanced Data Pipelines
Dive into the world of data engineering with "ETL Fundamentals for Advanced Data Pipelines," a course crafted for those aspiring to master ETL processes and build sophisticated data pipelines. This comprehensive course offers a blend of theory, case studies, and hands-on experience, guiding you through the intricacies of ETL and its pivotal role in modern data architectures.
Module 1: Introduction to ETL and Data Pipelines
Explore the basics of ETL processes.
Understand their significance in data architecture through case studies like Volvo Cars, EDPR, and more.
Set course objectives and anticipated outcomes.
Module 2: Understanding Data Sources and Extraction Techniques
Delve into various data sources like SQL, NoSQL, APIs.
Learn fundamental data extraction methods.
Practical session on extracting data from diverse sources.
Module 3: Data Transformation Techniques
Grasp the principles of data transformation.
Techniques for data cleaning and normalization.
Advanced methods including data aggregation and pivoting.
Hands-on activity on transforming raw data.
Module 4: Data Loading Strategies
Gain insights into data warehouses and data lakes.
Explore efficient data loading techniques.
Compare incremental vs. full load strategies.
Practical exercise on loading data into storage systems.
Module 5: Designing and Managing ETL Pipelines
Learn architectural patterns for scalable ETL pipelines.
Focus on data quality and integrity management.
Strategies for optimizing ETL process performance.
Hands-on project on designing an ETL pipeline.
Module 6: Advanced ETL Concepts and Technologies
Introduction to real-time ETL processes.
Engage with big data technologies.
Automation and orchestration in ETL.
Implement a real-time ETL solution in a hands-on session.
Module 7: Final Project and Course Conclusion
Undertake a final project to build an end-to-end ETL pipeline.
Apply methodologies from enterprise-level projects.
Discuss best practices and common pitfalls in ETL.