Apache Airflow Training in Bangalore

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Instructor-Led Online Training Parameters

Course Highlights

  • Instructor-led Online Training
  • Access to the recorded sessions
  • Certified & Experienced Trainers
  • Course Completion Certificate
  • Digital Learning Material
  • 24x7 After Training Support

Apache Airflow Training in Bangalore Course Overview

Apache Airflow is an open-source platform primarily designed to schedule and monitor workflows. With the digital age producing large volumes of data every day, managing this data effectively and efficiently becomes crucial. Apache Airflow steps in by providing a robust platform for data management tasks. For professionals looking to expand their knowledge in this area, Multisoft Systems offers comprehensive Apache Airflow Training in Bangalore.

In an era dominated by data, understanding tools like Apache Airflow can make a significant difference in how businesses operate. Whether you're a seasoned professional or a newcomer, Our offered course is based on a few things such as the definition of Airflow, how it works, and the process of configuring Apache Airflow. However, you will also learn the techniques of creating plugins, making real dynamic pipelines, and applying advanced concepts of Apache Airflow.

Apache Airflow Course Objectives:
  • How to deal with the core functionalities such as DAGs, Tasks, Operators, and Workflows?
  • How to understand and apply advanced concepts of Apache Airflow such as XCOMs, Branching and SubDAGs?
  • What is the difference between Sequential, Local and Celery Executors
  • How to use Sequential, Local and Celery Executors?
  • How to use Apache Airflow in a Big Data ecosystem with the use of PostgreSQL, Hive, Elasticsearch?
  • How to create plugins to add functionalities to Apache Airflow?
  • How to use Docker with Airflow and different executors?
  • How to implement solutions using Airflow to real data processing problems?
  • How to install and configure Apache Airflow?
Apache Airflow Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • 24x7 After Training Support
Apache Airflow Course Target Audience
  • Data engineers who want to deploy their pipelines with the use of Airflow
  • Engineers who want to switch their careers from conventional schedulers
  • Professionals who want to add a hot & demanding technology to their resume
  • Professionals who want to learn basic and advanced concepts about Apache Airflow
Apache Airflow Course Prerequisites
  • You should have prior work experience in programming or scripting to pursue this Apache Airflow Training. You need at least 8 gigabytes of memory and VirtualBox installed. A VM of 3Gb needs to be downloaded. However, working experience in Python will help you a lot.
Apache Airflow Course Certification
  • Multisoft Systems will provide you with a training completion certificate after completing this Apache Airflow Training.

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Course Objective

  • How to deal with the core functionalities such as DAGs, Tasks, Operators, and Workflows?
  • How to understand and apply advanced concepts of Apache Airflow such as XCOMs, Branching and SubDAGs?
  • What is the difference between Sequential, Local and Celery Executors
  • How to use Sequential, Local and Celery Executors?
  • How to use Apache Airflow in a Big Data ecosystem with the use of PostgreSQL, Hive, Elasticsearch?
  • How to create plugins to add functionalities to Apache Airflow?
  • How to use Docker with Airflow and different executors?
  • How to implement solutions using Airflow to real data processing problems?
  • How to install and configure Apache Airflow?

Course Prerequisite

  • You should have prior work experience in programming or scripting to pursue this Apache Airflow Training. You need at least 8 gigabytes of memory and VirtualBox installed. A VM of 3Gb needs to be downloaded. However, working experience in Python will help you a lot.

Course Target Audience

  • Data engineers who want to deploy their pipelines with the use of Airflow
  • Engineers who want to switch their careers from conventional schedulers
  • Professionals who want to add a hot & demanding technology to their resume
  • Professionals who want to learn basic and advanced concepts about Apache Airflow

Apache Airflow Training in Bangalore Course curriculum

Course Content

  • Important Prerequisites 
  • Course Objectives 
  • Who am I? 
  • Development Environment

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  • Introduction
  • Why Airflow?
  • What is Airflow? 
  • How Airflow works?
  • Installing Airflow 2.0
  • The CLI in Airflow 2.0
  • What you need to know about the UI

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  • Introduction
  • What is DAG? 
  • Time to code your first DAG
  • DAG Skeleton
  • What is an Operator?
  • Creating Table
  • The secret weapon!
  • The Providers
  • Is API available?
  • Extracting users
  • Processing users
  • Storing users
  • Order matters!
  • You data pipeline in action!
  • Dag scheduling
  • Backfilling and catchup

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  • Introduction
  • The default configuration 
  • Start scaling with the Local Executor
  • Scale to the infinity with the Celery Executor
  • Scaling Airflow with the Celery Executor in action!
  • Changing the executor
  • Concurrency, the parameters you must know!
  • Concurrency in practice

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  • Introduction
  • Adios repetitive patterns
  • Minimising DAGs with SubDAGs
  • Adios SubDAGs, Welcome TaskGroups!
  • Sharing data between tasks with XComs
  • XComs in action!
  • Choosing a specific path in your DAG
  • Executing a task according to a condition
  • Trigger rules or how tasks get triggered
  • Changing the way your tasks are triggered

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  • Introduction
  • Installing Elasticsearch
  • How the plugin system works?
  • Creating a hook interacting with Elasticsearch
  • Creating the PostgresToElasticOperator

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  • Introduction
  • Quick Reminder About Docker
  • Running Airflow on Docker with the Celery Executor
  • Running Airflow on Docker with the Local Executor

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  • What to expect from Airflow 2.0?

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Apache Airflow Corporate Training

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  • Certificate with Date of Issuance
  • Name and Digital Signature of the Awardee
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