Apache Airflow:Mastering Key Concepts And Conquer Challenges

Building of better data pipelines by overcoming with day to day challenges

What you'll learn

Understand the features and benefits of using Airflow for workflow orchestration.

Acquire troubleshooting skills for common installation issues and debugging setup problems

Understand the architecture and components of Apache Airflow.

Develop skills in handling complex dependencies and parallelism in DAG design.

Implement custom operators and sensors for seamless integration with specific systems or APIs.

Leverage XCom for efficient data exchange between tasks.

Develop skills in designing complex SubDAGs and managing dynamic workflow structures.

Implement Incremental Data Processing with a custom Airflow Operator.

Requirements

Any python version which is above 3.7 preferably pycharm

Latest version of Visual Studio Code application

Basic knowledge of python

Description

This course is meticulously crafted to provide you with a deep understanding of Apache Airflow, from the fundamentals to advanced concepts. Whether you're a beginner or a seasoned professional, this course equips you with the skills needed to orchestrate complex data workflows efficiently.Module 1: Introduction and Installation Embark on your Airflow journey with a solid foundation. Gain insights into Airflow's features and benefits, and master the art of installing and configuring Airflow in various environments. Dive into challenging resolution topics, troubleshooting installation issues, and debugging setup problems.Module 2: Workflow Design and Management Explore the intricacies of Airflow's architecture and components. Learn to define and structure workflows using Directed Acyclic Graphs (DAGs). Grasp task dependencies, scheduling techniques, and how to manage workflow execution, retries, and Service Level Agreements (SLAs). Tackle challenges in handling complex dependencies and parallelism in DAG design.Module 3: Operators and Sensors Navigate the diverse world of operators in Airflow, including BashOperator, PythonOperator, and SQLOperator. Harness the power of sensors to trigger tasks based on external events or conditions. Confront challenges by implementing custom operators and sensors for seamless integration with specific systems or APIs.Module 4: Advanced Concepts and Scaling Elevate your expertise with advanced workflow concepts, such as SubDAGs and branching workflows. Leverage XCom for efficient data exchange between tasks. Work with connections and variables in Airflow, and scale Airflow to handle large workloads while optimizing performance. Create a machine learning framework for executing specific tasks within the workflow. Conquer challenges in designing complex SubDAGs and managing dynamic workflow structures.Module 5: Incremental Data Load Delve into Incremental Data Processing and understand efficient strategies. Learn to implement Incremental Data Processing with a custom Airflow Operator. Explore techniques for efficient transformation and loading, ensuring optimal data processing strategies.Enroll now to unlock the full potential of Apache Airflow, conquer challenges, and become a master orchestrator of data workflows!

Overview

Section 1: Introduction and Installation

Lecture 1 Introduction to Airflow

Lecture 2 Overview of Airflow features and benefits

Lecture 3 DAG Important Concepts

Lecture 4 Installing and configuring Airflow on local environments

Lecture 5 Installation Challenges

Section 2: Workflow Design and Management

Lecture 6 Understanding Apache Airflow architecture and components

Lecture 7 Apache Airflow Executors : A comprehensive guide

Lecture 8 Examining the example DAG and guide to create a DAG

Lecture 9 Part 1: Creating a simple DAG in Apache Airflow

Lecture 10 Part 2: Creating a complex DAGs in Apache Airflow

Lecture 11 Task dependencies and Scheduling

Lecture 12 Managing Workflow Execution, Retries and SLAs

Lecture 13 Handling Complex Dependencies and Parallelism in DAGs

Section 3: Operators and Sensors

Lecture 14 Introduction to Operators in Apache Airflow

Lecture 15 Deep dive into common Operators

Lecture 16 Introduction to Sensors in Apache Airflow

Lecture 17 Custom Operators and Sensors

Lecture 18 Use cases of custom Operators and Sensors in Apache Airflow

Lecture 19 Custom Operator - Jinja template

Section 4: Advanced Concepts and Scaling

Lecture 20 Introduction to SubDAGs and Branching

Lecture 21 Data Exchange in Airflow with XCom

Lecture 22 Mastering Connections and Variables in Airflow

Lecture 23 Scaling and Optimizing Apache Airflow

Lecture 24 Understanding of Machine Learning

Lecture 25 Integrating ML workflows in Apache Airflow

Lecture 26 Challenges in Advanced Airflow Workflows and their Resolutions

Section 5: Incremental Data Load

Lecture 27 Understanding Incremental Data Processing

Lecture 28 Incremental Data Processing with Custom Airflow Operator

Lecture 29 Efficient Transformation and Loading Strategies

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