Apache Airflow: Core Concepts and Building Blocks

Hi, my name is Dmitrii Polovinkin, I'm a data engineer with ~7 years of experience (check out ⁠⁠my LinkedIn⁠⁠) and welcome to the first episode of Data Engineering Concepts, which is a new educational podcast about data engineering, designed to be useful when you're learning on the go. In this episode, I explain what Apache Airflow is, what problems it solves, and when it makes sense to use it in data engineering. We go through the main Airflow concepts, including DAGs and DAG runs, tasks and task instances, operators, sensors, hooks, connections, variables, scheduling, data intervals, XComs, and trigger rules. I also give a high-level overview of Airflow architecture, executors, workers, the metadata database, and some of the key DAG configuration parameters. If you find this episode useful, consider following the podcast and leaving a rating or review! 🎙️ Data Engineering Concepts — making complex data engineering topics easier to understand, one episode at a time. Podcast website: 🌐 ⁠⁠⁠https://deconcepts.com⁠⁠⁠ Add me on LinkedIn: ⁠⁠https://www.linkedin.com/in/dpolovinkin⁠⁠