I was considering introducing MWAA in order to separate the existing scheduler in the company and manage the execution history, etc., and I took this lecture. When I had no idea how to start airflow, I wrote the code, configured the local docker environment, and created the DAG, and I got a good sense of how to use it.
It may not be easy to find the best practice for each platform in the operating environment, but I think I acquired basic knowledge that I can touch on various things by reading the official documentation. Thank you.
5.0
ground
35% 수강 후 작성
It seems like a lecture that lets you know what tools data engineers use and what those tools do. I will keep going. Thank you for always making good lectures.
5.0
소연
100% 수강 후 작성
I signed up for the course because I wanted to use it well in my work. It seemed like a perfect fit for basic study. I liked that it was focused on practical training.
강의상세_배울수있는것_타이틀
Build a data pipeline
Apache Airflow
Introduction to Apache Spark
Introducing MinIO
TaskFlow API
Slack Integration
Airflow, an essential tool for data pipelines Learn from Silicon Valley developers! 🔥
Modern data workflow management, With Apache Airflow 📌
The most used workflow management tool in the field: Apache Airflow
Learn the simple setup and usage of Airflow. We'll guide you through creating your first data workflow.
Leave complex concepts behind and dive into the fascinating world of Airflow!
As data analysis and processing tasks become more complex , issues such as job scheduling, dependency management, and error handling become more important. To effectively address these challenges, Airflow is one of the core tools of choice for many organizations.
This lecture is a lecture prepared in advance for those who are new to Airflow. Apache Airflow, which is popular in Silicon Valley. I will help you get started in a simple and easy way.
Why should you learn Apache Airflow?
Automated workflow management
Airflow provides powerful scheduling capabilities to automatically run and manage tasks over time. You can plan and execute data processing tasks more efficiently.
Dependency Management
Complex data workflows require precise management of dependencies between tasks. Airflow provides the ability to clearly define dependencies between tasks and specify the order of tasks.
Powerful monitoring and notifications
You can monitor the progress of your jobs through the Airflow dashboard while your jobs are running. You can also set up alerts to respond quickly if your jobs fail or encounter issues.
Scalability and flexibility
Airflow supports a variety of plugins and libraries. It can integrate with various data stores, job execution environments, and notification mechanisms. Build custom workflows to fit your needs.
Community and Ecosystem
Airflow has a vibrant community and rich ecosystem, so there are a lot of great resources to help you troubleshoot.
Lecture Features ✨
✅ Easy to understand without difficult concepts! Explains what Airflow is and why it is needed through analogies and examples .
✅A hands-on course that follows the actual Airflow usage process and creates a simple data workflow!
✅If you have any questions or do not understand anything during the lecture, please feel free to ask questions at any time. Learn with Q&A !
What you'll learn 📚
All lecture materials are in English. The lectures themselves are conducted in Korean and are designed to facilitate future overseas employment.
We provide PDF lecture materials and Github code.
Cloud Software Architecture Overview
Introduction to Data Pipeline Orchestrator
Introduction to Apache Airflow
Introduction to the key components of Apache Airflow
Detailed introduction of each component
Detailed analysis of the code
We will share with you the know-how of current Silicon Valley engineers!
I am a current software engineer who runs YouTube's " American Engineer " and Brunch's " Silicon Valley News and Life ." I graduated from the University of California, Berkeley EECS and am currently working on big data at the headquarters of a global big tech company in Silicon Valley. I would like to share the know-how I have learned from my actual work with many people. 🙂
If you are this type of person Get started right now.
💡
Data Engineer
Automate and schedule data workflows to maintain data quality and consistency .
💡
Data Analyst
Try handling tasks like regular data updates or model retraining .
💡
Data Scientist
Efficiently manage your data science process by automating model training, evaluation, batch predictions, and more .
💡
system administrator
It can increase transparency and reliability of work execution.
💡
Data Engineering and Development Team
You can implement various automated tasks such as ETL(Extract, Transform, Load)tasks and API calls .
💡
Project Manager
You can effectively adjust your project schedule by setting task dependencies, priorities, expected execution times, etc.
Expected Questions Q&A 💬
Q. Why should I learn Apache Airflow?
Apache Airflow is a data workflow management tool used to automate, schedule, and monitor data pipelines. It can efficiently manage data workflows for various roles such as data engineers, data scientists, and system administrators.
In the latter half of the lecture, you will learn how to integrate with big data technology (Apache Spark), which will be of great help to data engineers who manage many pipelines.
Q. Is this a lecture that non-majors can also take?
If you are not a major but know the basics of Python and want to improve the efficiency of your data or task scheduling workflow, this will be of great help.
If you are new to Python, learn the basics of Python through YouTube or take the lecture below first! Even if you only watch the basics, you will have no trouble following the entire lecture.
Q. Is there anything I need to prepare before attending the lecture?
Since the code is written in Python, there will be no basic Python lectures. Also, there will be practical training using Docker, so it will be easier to understand if you have basic knowledge of Docker.
Things to note before taking the class 📢
Practice environment
Operating System and Version (OS)
The course will be taught on MacOS, but you can follow the exercises on any operating system that has Python (Airflow itself is a Python library).
Tools to use
Python 3.7+
Airflow is Apache licensed, so it's free.
PC specifications
CPU: 2 cores or more
Memory: 4GB or more
Disk: 10GB or more
Player Knowledge and Notes
Basic knowledge of Python and Docker is required, and the environment for this lecture is set up with Docker. If you want to know more about Docker, I recommend you refer to my free Docker lecture . Lecture link: [ https://inf.run/8eFCL ]
If you have any questions, please feel free to ask. However, since I am located in the western United States, it may take some time for me to respond.
강의소개.콘텐츠.추천문구
학습 대상은 누구일까요?
Data Engineer
If you want to become a data engineer
선수 지식, 필요할까요?
Python
강의소개.지공자소개
20,804
수강생
1,047
수강평
337
답변
4.8
강의 평점
29
강의_other
Are you going to finish in Korea? Penetrate the global market with English!🌍🚀
Hello. I majored in Computer Science (EECS) at UC Berkeley💻, have worked as a software engineer in Silicon Valley for over 15 years, and am currently a Staff Software Engineer working with Big Data and DevOps at a Big Tech headquarters in Silicon Valley.
🧭 I would now like to share the technologies and know-how I learned firsthand at the forefront of innovation in Silicon Valley with all of you through online lectures.
🚀 Join me, having learned and grown at the forefront of technological innovation, and develop the skills to compete on the global stage!
🫡 I may not be the smartest, but I want to emphasize that you can achieve anything if you stay consistent and never give up. I will always be by your side, supporting you with great resources.
Hello Gong16,
Thank you for taking the time to leave such a great review. I'm glad to hear that it was easy to understand! I'm happy that you seem satisfied with the lecture.