When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Automate Data Pipelines: Schema Evolution

This course is part of LLM Optimization & Evaluation Specialization

Instructor: LearningMate

Included with

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build automated data pipelines with Apache Airflow, manage schema evolution to prevent failures, and implement monitoring for data integrity.

Skills you'll gain

Tools you'll learn

Apache Airflow

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the LLM Optimization & Evaluation Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

Automate Data Pipelines: Schema Evolution is an intermediate course designed for data engineers, analysts, and developers looking to build robust, failure-resistant data workflows. In today's dynamic data landscape, pipelines often break when source data structures change unexpectedly—a problem known as schema drift. This course tackles that challenge head-on, teaching you how to design and automate data pipelines that can gracefully handle schema evolution using Apache Airflow.

You will gain hands-on experience designing, building, and scheduling complex data pipelines (DAGs) that automate ETL processes from extraction to loading. The curriculum places a strong emphasis on creating idempotent workflows that detect and adapt to schema changes, ensuring data integrity and preventing costly failures. Through practical labs and real-world case studies from companies like Uber and BharatPe, you will implement data validation checks and build comprehensive monitoring and alerting systems. By the end of this course, you will be equipped to create resilient, scalable, and fully automated data pipelines that are built to withstand the complexities of real-world data environments.

Module details

This module provides a deep dive into the world of workflow automation with Apache Airflow. You will move from understanding the core concepts of DAGs and operators to building a complete, scheduled data pipeline in a hands-on lab. The focus is on creating robust, idempotent workflows that form the backbone of reliable data systems.

What's included

1 video2 readings2 assignments

Data sources are not static. This module addresses the critical skill of managing schema evolution. You will learn how to analyze the downstream impact of source data changes and use dbt to adapt your data quality tests, ensuring your pipelines remain robust and trustworthy even as data structures evolve.

What's included

2 videos2 readings2 assignments

2 videosTotal 10 minutes

The Silent Pipeline Killer: Schema Drift4 minutes
Writing and Adapting dbt Tests5 minutes

2 readingsTotal 7 minutes

Understanding Schema Drift and Data Lineage3 minutes
How-To: Documenting and Communicating Schema Changes4 minutes

2 assignmentsTotal 17 minutes

Hands-On Learning: Handling Schema Evolution with dbt Testing12 minutes
Knowledge Check: Schema Impact5 minutes

This module extends beyond building pipelines to tackle "silent failures"—where a successful run produces bad data—and establishes observability as the core defense. You will instrument Airflow DAGs to emit key health metrics like freshness, volume, and duration, and configure automated alerts using on_failure_callback. By the end, you will construct resilient pipelines that fail loudly, ensuring data integrity and stakeholder trust.