Why This Training?
In an age where data drives decisions, the need to efficiently manage, schedule, and orchestrate complex workflows becomes paramount. Apache Airflow stands out as a potent tool designed for these challenges. This training unravels the intricacies of Airflow, guiding participants to master the art of data workflow orchestration and transform their data operations.
Duration: 9 Hours (online / virtual live session)

Who Should Attend?

 Data engineers seeking to streamline data workflows.
 Data scientists aiming for smoother model training and deployment pipelines.
 DevOps professionals enhancing automation capabilities.
 IT managers and decision-makers overseeing data infrastructure.
 Anyone enthusiastic about workflow orchestration and automation in the data realm.

Course Highlights

 Foundational Grasp: Dive deep into the significance of workflow orchestration and Airflow's core concepts.
 Hands-on Setup & Deployment: Learn to set up Airflow and write your first DAG.
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 Advanced Techniques: Master operators, monitoring tools, and logging methods.
 Scalability & Security: Scale your Airflow setup and ensure utmost security.
 Integration Know-how: Seamlessly connect Airflow with popular data tools and platforms.
 Industry Best Practices: Imbibe best practices for efficient pipeline design and error handling.
 Peek into the Future: Stay ahead by understanding Airflow's upcoming features and trends.
 Interactive Discussions & Q&A: Engage in stimulating discussions and get your queries resolved by experts.


 A foundational understanding of data operations and processes.
 Familiarity with basic programming concepts.
 Prior experience with database systems will be beneficial but not mandatory.

Training Materials Needed by Participants

A laptop or computer with a stable internet connection.
Apache Airflow software (installation guide will be provided).
Any modern web browser (Chrome, Firefox, Safari).
Access to a text editor or IDE for writing and editing code.
Recommended: Access to a text editor or IDE for writing and editing code.
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Training Content

Apache Airflow: Mastering Data Workflow Orchestration

1. Foundations of Workflow Orchestration with Apache Airflow

Objective: Establish the significance of workflow orchestration and introduce Apache Airflow.
1.1 Introduction to Workflow Orchestration
  • The essence of workflow orchestration
  • Evolution of orchestration tools
1.2 Deep Dive into Apache Airflow
  • Core concepts: DAG, Operator, Task, Executor
  • How Airflow stands apart from other tools
1.3 Setting Up & Writing Your First DAG
  • Installation, database initialization, web server, and scheduler
  • Writing and understanding a basic DAG

2. Advanced Orchestration Techniques with Airflow

Objective: Delve into Airflow’s advanced capabilities and enhance monitoring and security understanding.
2.1 Operators in Airflow
  • Overview of key operators
  • Custom operator development

2.2 Monitoring, Logging, and Debugging
  • Airflow UI for task monitoring
  • Using logs effectively
2.3 Advanced Features & Scaling Airflow
  • Dynamic DAGs, SubDAGs, TaskGroups, and XComs
  • Different Executors and scaling with Celery

3. Integrations, Best Practices, and Future Directions

Objective: Understand how Airflow integrates with other tools, grasp best practices, and foresee future trends.
3.1 Securing Apache Airflow
  • Role-based access and authentication backends
  • Ensuring web server security

3.2 Integrating Airflow with Data Tools & Platforms
  • Using hooks, cloud integrations, and interfacing with platforms like Databricks

3.3 Best Practices, Use Cases, and Real-world Scenarios
  • Efficient pipeline design, error han

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