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Data Engineering Concepts

Dmitrii Polovinkin

Data Engineering Concepts is a podcast about the tools, technologies, and ideas that data engineers work with every day. In relatively short episodes I break down one topic at a time - describing how modern data stack works. Practical explanations, real-world context, and lessons from 7 years of working in data engineering.

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  • 2 episodes
  • Avg 19 min
  • English

Episodes 2

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  • #1
    Today · 29 min

    Apache Airflow

    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.

  • September 5 · 9 min

    Pilot - Welcome to Data Engineering Concepts

    Hi, my name is Dmitrii Polovinkin, I'm a data engineer with ~7 years of experience (check out ⁠my LinkedIn⁠) and welcome to the pilot 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 why I started the podcast, about my experience as a DE, who it is for, what topics future episodes will cover, and how I plan to approach them. If you're a data engineer or interested to become one, work in a related field or preparing for interviews - subscribe, this podcast is for you! This is episode zero is recorded in Da Nang, Vietnam 🇻🇳.

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