এই পডকাস্টটি সম্বন্ধে 🔗
Welcome to The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI— the podcast where we keep you up to date with insights and ideas propelling the Airflow community forward.
Join us each week, as we explore the current state, future and potential of Airflow with leading thinkers in the community, and discover how best to leverage this workflow management system to meet the ever-evolving needs of data engineering and AI ecosystems.
Podcast Webpage: https://www.astronomer.io/podcast/
Join us each week, as we explore the current state, future and potential of Airflow with leading thinkers in the community, and discover how best to leverage this workflow management system to meet the ever-evolving needs of data engineering and AI ecosystems.
Podcast Webpage: https://www.astronomer.io/podcast/
উপস্থাপক:
আপডেট ফ্রিকোয়েন্সি:
weekly
গড় অডিও দৈর্ঘ্য:
27 minutes
ইংরেজি
মার্কিন যুক্তরাষ্ট্র
121 পর্ব
19 জানুয়ারি, 2018থেকে
episodic
সাম্প্রতিক এপিসোড 🔗
At Lyft, a small data engineering team supports dozens of scientists and analysts who tune driver pay configurations on demand, all under SOX controls. In this episode, Ken Obata, Senior Software Engineer at Lyft, joins Kenten Danas to walk through how his team built self-service Dags with an event…
অতীতের এপিসোডগুলি অনুসন্ধান করুন
The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI এর অতীতের এপিসোডগুলি অনুসন্ধান করুন।
পূর্ববর্তী এপিসোডসমূহ 🔗
Running Airflow with a one-person data engineering team means every decision about cost, tooling, and best practices has to earn its keep. In this episode, Kenten sits down with Aniruddha Sengupta, Staff Data Engineer at Insignis, to talk through how the UK cash-savings fintech runs a low-cost, sca…
Scaling Airflow to over 1,000 active DAGs on a team of 3-4 engineers takes structure. In this episode, Kenten Danas talks with Matt Stavinga, Data Engineer at Idelic (now part of Descartes), about how his team standardized DAG creation and logging, built a Jenkins-driven testing workflow with per-P…
Running LLMs over sensitive data means external APIs are off the table, but open-weight models still need reproducibility, validation, and a paper trail before downstream systems can depend on their output. In this episode, Kenten is joined by Chhayank Jain, Senior ML Engineer at Visa, to talk thro…
Security is one of the least visible parts of Airflow for most users, but it shapes what features teams can turn on in production. In this episode, Kenten Danas talks with Anish Giri, Senior Software Engineer and active Apache Airflow contributor focused on security, about three recent contribution…
Orchestrating data across more than 30 companies means most Airflow users on the platform aren't data engineers. In this episode, Kenten Danas talks with Lucas Trubiano, Data Engineer at itti, the technology company within Grupo Vázquez in Paraguay. Lucas walks through the custom YAML framewor…
Manufacturing data pipelines can't afford silent failures. When quality decisions and shop-floor visibility depend on Airflow, a broken DAG at midnight can cost real money. In this episode, Kenten Danas talks with Kumuda Sreenivasa, Founder of Receitly and Senior Data Architect at ATC Drivetra…
Strict sequential execution across DAGs sounds simple until you have scheduled pipelines and event-driven pipelines writing to the same MongoDB collections. Ivana Isailovic, Senior Big Data Engineer at Synechron, joins Marc Lamberti to walk through the three-layer DAG architecture her team built to…
Financial data pipelines have to be right the first time. On this episode, Kenten sits down with [Antonello Benedetto](linkedin.com/in/anbento4), Staff Data Engineer at Wise, to talk about how the central data and analytics engineering team runs Airflow for critical financial datasets, tiers pipeli…
Running a travel platform means dealing with fast-moving inventory, real-time fraud detection, and heavy performance marketing attribution, all while keeping data trustworthy for a data-driven org. In this episode, Mrinalini Singh, Data Platform Engineer at [Headout](headout.com), walks through how…
দাবি পরিত্যাগ: এই পৃষ্ঠায় এম্বেড করা পডকাস্ট এবং আর্টওয়ার্ক Astronomer থেকে এসেছে, যা এর মালিকের সম্পত্তি এবং Listen Notes, Inc দ্বারা অনুমোদিত বা অনুমোদিত নয়৷
পডকাস্ট সার্চ ইঞ্জিন
আপনি আমাদের ওয়েবসাইট ব্যবহার করতে পারেন3,828,910পডকাস্ট এবং196,504,053পর্বগুলি মানুষ, স্থান, বা বিষয় দ্বারা অনুসন্ধান করতে৷
If I have seen further than others, it is by listening to podcasts and standing upon the shoulders of
giants.
‐ Isaac "Llamacorn" Newton
অতীতের এপিসোডগুলি অনুসন্ধান করুন
The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI এর অতীতের এপিসোডগুলি অনুসন্ধান করুন।
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