Apache Airflow + AWS instance :DAG, Task, Task Instance & Operators practically executed | Hindi

💡 What You'll Learn: ✅ What is a DAG in Airflow? ✅ Understanding Tasks & Task Instances ✅ Different types of Operators and their role in DAG execution ✅ How to define, schedule, and monitor DAGs ✅ Real-world use cases in ETL & Data Pipelines Unlock the power of Apache Airflow with this deep dive into DAGs, Tasks, Task Instances, and Operators. This video also teachs you how to check for logs in Apache Airflow 🚀 This video is a must-watch for Data Engineers, ETL Developers, and Big Data professionals looking to master workflow orchestration using Airflow. 0:00 - Intro to session 0:22 - AWS instance + DAG hands-on practical, airflow webserver and airflow scheduler 3:40 - Configure DAG folder in Airflow via EC2 instance terminal 11:39 -Important FAQs for DAGs in Airflow 18:28 - Tasks, Task Instances and Operators in Apache Airflow By the end of this video, you'll be ready to implement Apache Airflow DAGs efficiently in your data engineering projects. What does the Data Engineering ecosystem consists of..? -- Airflow, Azure, DataBricks, AWS EMR, Glue, Lambda, Kinesis, Spark-Streaming, Python Programming, Apache Hadoop, Apache Hive, PySpark, SparkSQL, Kafka, etc.. Request a Call Back from Us to know about the full stack courses in Data Engg and career support Google Forms- https://forms.gle/BFRskqhD3GVNSV5U6 Detailed syllabus of Data Engineering Stack with Airflow, AWS, Azure DataBricks, Apache Spark 3, Kafka, Hive Link : https://versiontwo.tg117.in/course/ 🔥 Don't forget to LIKE, SHARE & SUBSCRIBE for more Apache Airflow tutorials!