Apache Airflow For Workflow Orchestration Training Course: Automate Data Workflows

Introduction

Streamline your data pipelines with our Apache Airflow for Workflow Orchestration Training Course. This program is designed to equip you with the essential skills to build and manage complex data workflows, enabling you to automate and monitor your data processing tasks efficiently. In today's data-driven world, mastering workflow orchestration is crucial for organizations seeking to manage intricate data pipelines and ensure data reliability. Our Apache Airflow training course offers hands-on experience and expert guidance, empowering you to leverage Airflow's capabilities for diverse data engineering and analytics tasks.

This automate data workflows training delves into the core concepts of Apache Airflow, covering topics such as Directed Acyclic Graphs (DAGs), task scheduling, and workflow monitoring. You'll gain expertise in using industry-standard techniques to build and manage complex data workflows, meeting the demands of modern data-intensive organizations. Whether you're a data engineer, data scientist, or DevOps engineer, this Apache Airflow for Workflow Orchestration course will empower you to design and implement robust and scalable data pipelines.

Target Audience:

• Data Engineers
• Data Scientists
• DevOps Engineers
• Data Analysts
• System Administrators
• Software Developers
• Anyone needing Apache Airflow skills

Course Objectives:

• Understand the fundamentals of Apache Airflow for workflow orchestration.
• Master DAG (Directed Acyclic Graph) creation and management.
• Utilize Airflow operators for various data processing tasks.
• Implement task scheduling and dependency management.
• Design and build complex data workflows with Airflow.
• Optimize Airflow configurations for performance and reliability.
• Troubleshoot and address common issues in Airflow deployments.
• Implement data quality checks and validation in Airflow workflows.
• Integrate Airflow with various data storage and processing systems.
• Understand how to handle large datasets and distributed processing with Airflow.
• Explore advanced Airflow features (e.g., custom operators, sub-DAGs).
• Apply real world use cases for Apache Airflow in data engineering.
• Leverage Airflow's ecosystem for efficient workflow management.

Duration

10 Days

Course content

Module 1: Introduction to Apache Airflow

• Fundamentals of Apache Airflow for workflow orchestration.
• Overview of DAGs, operators, and task scheduling.
• Setting up an Airflow development environment.
• Introduction to Airflow architecture and components.
• Best practices for Airflow.

Module 2: DAG Creation and Management

• Mastering DAG (Directed Acyclic Graph) creation and management.
• Utilizing Python for DAG definition.
• Designing and building complex DAGs with dependencies.
• Optimizing DAGs for workflow efficiency.
• Best practices for DAG creation.

Module 3: Airflow Operators

• Utilizing Airflow operators for various data processing tasks.
• Implementing operators for data ingestion, transformation, and loading.
• Designing and building custom operators.
• Optimizing operators for specific data processing needs.
• Best practices for Airflow operators.

Module 4: Task Scheduling and Dependencies

• Implementing task scheduling and dependency management.
• Utilizing Airflow schedulers and triggers.
• Designing and building scheduled workflows.
• Optimizing task dependencies for workflow reliability.
• Best practices for scheduling.

Module 5: Complex Data Workflows

• Designing and building complex data workflows with Airflow.
• Implementing branching and looping in workflows.
• Utilizing sub-DAGs and external task dependencies.
• Optimizing workflows for specific data pipelines.
• Best practices for complex workflows.

Module 6: Airflow Configuration Optimization

• Optimizing Airflow configurations for performance and reliability.
• Utilizing Airflow configuration parameters.
• Implementing resource management and scaling.
• Designing efficient Airflow deployments.
• Best practices for configuration optimization.

Module 7: Troubleshooting Airflow Deployments

• Debugging common issues in Airflow deployments.
• Analyzing Airflow logs and error messages.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common deployment errors.
• Best practices for troubleshooting.

Module 8: Data Quality Checks and Validation

• Implementing data quality checks and validation in Airflow workflows.
• Utilizing Airflow sensors and checks.
• Designing and building data quality workflows.
• Optimizing validation for data integrity.
• Best practices for data quality.

Module 9: Integration with Data Systems

• Integrating Airflow with various data storage and processing systems.
• Utilizing Airflow hooks and connections.
• Implementing data integration with external databases and APIs.
• Optimizing integration for data retrieval and processing.
• Best practices for integration.

Module 10: Large Datasets and Distributed Processing

• Understanding how to handle large datasets and distributed processing with Airflow.
• Utilizing Airflow with distributed computing frameworks.
• Implementing data partitioning and parallel processing.
• Designing scalable data processing workflows.
• Best practices for large datasets.

Module 11: Advanced Airflow Features

• Exploring advanced Airflow features (custom operators, sub-DAGs).
• Utilizing custom operators for specialized tasks.
• Implementing sub-DAGs for modular workflows.
• Designing and building advanced Airflow solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced features.

Module 12: Real-World Use Cases

• Implementing Airflow for ETL/ELT pipelines.
• Utilizing Airflow for machine learning workflows.
• Implementing Airflow for data warehousing automation.
• Utilizing Airflow for log processing and data analysis.
• Best practices for real-world applications.

Module 13: Airflow Tools Implementation

• Utilizing Airflow tools and frameworks (Airflow UI, Airflow CLI).
• Implementing Airflow workflows with specific tools.
• Designing and building automated deployment workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Workflow Monitoring and Logging

• Implementing workflow monitoring and logging in Airflow.
• Utilizing Airflow monitoring tools and metrics.
• Designing and building performance dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in Airflow Orchestration

• Emerging trends in Airflow orchestration.
• Utilizing AI for workflow automation.
• Implementing Airflow in cloud-native environments.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.