As Large Language Models (LLMs) evolve, building smart AI systems isn’t just about prompt engineering anymore — it's about connecting data pipelines, orchestrating multi-stage tasks, and deploying reliable, scalable applications. This is where GenAI ...
No module named ‘airflow\.providers.postgres.operators’ — and why using SQLExecuteQueryOperator saved the day The Frustrating Error That Blocked My DAGs If you’ve ever set up Apache Airflow in Docker and tried to use the Postgres operator in your DAG...
Apache Airflow can seem intimidating at first, with its steep learning curve and occasional setup errors. However, once you get it running on your machine, the sense of achievement is unparalleled, especially for beginners. This guide provides a clea...
Have you ever looked at stock charts and wondered what goes on behind the scenes to make them work? Maybe not, but I did, especially after starting crypto trading late last year. That curiosity led me, a few weeks back, to start a personal data engin...
Data Engineering Foundations: A Hands-On Guide Hey there! If you’ve been curious about data engineering, this guide will help you understand the basics and walk you through practical examples. Whether it’s setting up storage, processing data, automat...
Apache Airflow is a powerful open-source platform designed to author, schedule, and monitor workflows. It has become a popular choice for orchestrating ETL pipelines and machine learning workflows due to its extensible framework and robust tracking c...
1. Installing Airflow via pip 🛠️ Boilerplate Code: pip install apache-airflow Use Case: Install Apache Airflow to automate workflows and tasks. Goal: Set up Airflow for task automation on your local environment. 🎯 Sample Code: pip install apache-a...
Introduction to Data Pipeline 데이터 파이프라인은 원시 데이터 (Raw Data) 를 수집하여 유용한 정보로 변환하는 일련의 프로세스를 말합니다. 데이터의 수집, 저장, 처리, 분석, 그리고 시각화까지의 전 과정을 포함하며, Big Data 환경에서는 대용량 데이터의 효율적인 처리를 위해 필수적인 요소입니다. 데이터 파이프라인의 주요 구성 요소 데이터 수집 (Data Ingestion) 데이터 저장 (Data ...
1. Introduction to Airflow 2. Key Concepts and Terminology 3. Installing and Setting Up Airflow 4. Understanding Directed Acyclic Graphs (DAGs) 5. Creating Your First DAG 6. Operators, Sensors, and Hooks 7. Managing Dependencies 8. Scheduling and Tri...
In the rapidly evolving landscape of data engineering, orchestrating and automating complex workflows has become a fundamental necessity. Businesses are increasingly dependent on data-driven insights, requiring robust systems to manage the seamless f...
