Mastering Apache Airflow

DOWNLOAD

Download Mastering Apache Airflow PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Mastering Apache Airflow book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Mastering Apache Airflow

DOWNLOAD
Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date :

Mastering Apache Airflow written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.

Empower Your Data Workflow Orchestration and Automation Are you ready to embark on a journey into the world of data workflow orchestration and automation with Apache Airflow? "Mastering Apache Airflow" is your comprehensive guide to harnessing the full potential of this powerful platform for managing complex data pipelines. Whether you're a data engineer striving to optimize workflows or a business analyst aiming to streamline data processing, this book equips you with the knowledge and tools to master the art of Airflow-based workflow automation.

Apache Airflow Best Practices

DOWNLOAD
Author : Dylan Intorf
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-31

Apache Airflow Best Practices written by Dylan Intorf and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-31 with Computers categories.

Confidently orchestrate your data pipelines with Apache Airflow by applying industry best practices and scalable strategies Key Features Seamlessly migrate from Airflow 1.x to 2.x and explore the key features and improvements in version 2.x Learn Apache Airflow workflow authoring through practical, real-world use cases Discover strategies to optimize and scale Airflow pipelines for high availability and operational resilience Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData professionals face the challenge of managing complex data pipelines, orchestrating workflows across diverse systems, and ensuring scalable, reliable data processing. This definitive guide to mastering Apache Airflow, written by experts in engineering, data strategy, and problem-solving across tech, financial, and life sciences industries, is your key to overcoming these challenges. Covering everything from Airflow fundamentals to advanced topics such as custom plugin development, multi-tenancy, and cloud deployment, this book provides a structured approach to workflow orchestration. You’ll start with an introduction to data orchestration and Apache Airflow 2.x updates, followed by DAG authoring, managing Airflow components, and connecting to external data sources. Through real-world use cases, you’ll learn how to implement ETL pipelines and orchestrate ML workflows in your environment, and scale Airflow for high availability and performance. You’ll also learn how to deploy Airflow in cloud environments, tackle operational considerations for scaling, and apply best practices for CI/CD and monitoring. By the end of this book, you’ll be proficient in operating and using Apache Airflow, authoring high-quality workflows in Python, and making informed decisions crucial for production-ready Airflow implementations.What you will learn Explore the new features and improvements in Apache Airflow 2.0 Design and build scalable data pipelines using DAGs Implement ETL pipelines, ML workflows, and advanced orchestration strategies Develop and deploy custom plugins and UI extensions Deploy and manage Apache Airflow in cloud environments such as AWS, GCP, and Azure Plan and execute a scalable deployment strategy for long-term growth Apply best practices for monitoring and maintaining Airflow Who this book is for This book is ideal for data engineers, developers, IT professionals, and data scientists looking to optimize workflow orchestration with Apache Airflow. It's perfect for those who recognize Airflow’s potential and want to avoid common implementation pitfalls. Whether you’re new to data, an experienced professional, or a manager seeking insights, this guide will support you. A functional understanding of Python, some business experience, and basic DevOps skills are helpful. While prior experience with Airflow is not required, it is beneficial.

Mastering Data Science

DOWNLOAD
Author : Bright Mills
language : en
Publisher: via tolino media
Release Date : 2025-07-31

Mastering Data Science written by Bright Mills and has been published by via tolino media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-31 with Computers categories.

Data Science offers a comprehensive exploration into the expansive world of data science, tailored for students, professionals, and enthusiasts seeking to build or deepen their understanding.

The Definitive Guide To Apache Airflow 3x

DOWNLOAD
Author : Frank Reiniger
language : en
Publisher: Independently Published
Release Date : 2025-11-19

The Definitive Guide To Apache Airflow 3x written by Frank Reiniger and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-19 with Computers categories.

The Definitive Guide to Apache Airflow 3x: Learn to Automate Pipelines, Scale Clusters, and Build Reliable Data Platforms Using Airflow 3 and Python 3 What would happen to your business if your data pipelines were faster, safer, and never failed silently? In a world where every decision is powered by data, brittle pipelines and outdated orchestration models can bring entire platforms to a halt. Airflow 3.x changes the game, and this book shows you exactly how to use it to transform your workflow ecosystem. At its core, this book gives you a practical, production-ready blueprint for mastering Apache Airflow 3.x. It solves the number-one pain engineers face today: building reliable, testable, observable, secure pipelines that can scale across teams and environments. No fluff, no theory, just real code, proven patterns, and fully runnable examples. You'll learn how to design and operate Airflow the way top data and MLOps teams do it today. The book guides you through modern Task SDK authoring, asset-driven DAG design, containerized execution, GitOps workflows, Kubernetes scaling strategies, observability pipelines, secrets management, and industry-grade security controls. It also includes a full Airflow 2→3 migration playbook and complete MLOps pipeline templates. By the time you finish, you'll know how to build Airflow platforms that are robust, reproducible, and easy to maintain, even at scale. What you'll gain inside this book: - The exact patterns for writing clean, testable Airflow 3 tasks and asset-driven DAGs. - Strategies for running Airflow on Kubernetes-pod templates, autoscaling workers, resource tuning, and HA schedulers. - Complete observability systems using Prometheus, Grafana, OpenTelemetry, and structured logging. - Hardened security setups with Vault, AWS KMS/SecretsManager, mTLS, network policies, and RBAC enforcement. - Fully scripted migration from Airflow 2.x to 3.x, including AST codemods and configuration upgrades. - End-to-end reproducible ML pipelines, dataset versioning, training, validation, storage, approvals, and deployment. - Real operational playbooks and admin scripts for debugging, backups, zombie-task cleanup, and data-platform automation. If you want to become the engineer who can architect, scale, and operate a production-grade Airflow platform, this is your manual. Take control of your data platform. Get the definitive Airflow 3.x guide today.

Cracking The Data Engineering Interview

DOWNLOAD
Author : Kedeisha Bryan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-11-07

Cracking The Data Engineering Interview written by Kedeisha Bryan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-07 with Computers categories.

Get to grips with the fundamental concepts of data engineering, and solve mock interview questions while building a strong resume and a personal brand to attract the right employers Key Features Develop your own brand, projects, and portfolio with expert help to stand out in the interview round Get a quick refresher on core data engineering topics, such as Python, SQL, ETL, and data modeling Practice with 50 mock questions on SQL, Python, and more to ace the behavioral and technical rounds Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPreparing for a data engineering interview can often get overwhelming due to the abundance of tools and technologies, leaving you struggling to prioritize which ones to focus on. This hands-on guide provides you with the essential foundational and advanced knowledge needed to simplify your learning journey. The book begins by helping you gain a clear understanding of the nature of data engineering and how it differs from organization to organization. As you progress through the chapters, you’ll receive expert advice, practical tips, and real-world insights on everything from creating a resume and cover letter to networking and negotiating your salary. The chapters also offer refresher training on data engineering essentials, including data modeling, database architecture, ETL processes, data warehousing, cloud computing, big data, and machine learning. As you advance, you’ll gain a holistic view by exploring continuous integration/continuous development (CI/CD), data security, and privacy. Finally, the book will help you practice case studies, mock interviews, as well as behavioral questions. By the end of this book, you will have a clear understanding of what is required to succeed in an interview for a data engineering role.What you will learn Create maintainable and scalable code for unit testing Understand the fundamental concepts of core data engineering tasks Prepare with over 100 behavioral and technical interview questions Discover data engineer archetypes and how they can help you prepare for the interview Apply the essential concepts of Python and SQL in data engineering Build your personal brand to noticeably stand out as a candidate Who this book is for If you’re an aspiring data engineer looking for guidance on how to land, prepare for, and excel in data engineering interviews, this book is for you. Familiarity with the fundamentals of data engineering, such as data modeling, cloud warehouses, programming (python and SQL), building data pipelines, scheduling your workflows (Airflow), and APIs, is a prerequisite.

Data Pioneers Unlocking Big Data Engineering Potential

DOWNLOAD
Author : Ravi Kumar Burila
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-06-19

Data Pioneers Unlocking Big Data Engineering Potential written by Ravi Kumar Burila and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-19 with Business & Economics categories.

The era of big data has revolutionized industries, but navigating its complexities requires a deep understanding of engineering principles and cutting-edge tools. Data Pioneers: Unlocking Big Data Engineering Potential serves as a comprehensive guide for data engineers and IT professionals eager to master the art and science of big data systems. This book covers the evolution of big data, emphasizing core concepts like structured, semi-structured, and unstructured data while introducing readers to essential frameworks, including Hadoop, Apache Spark, and Delta Lake. Dive into the design and architecture of scalable pipelines, comparing batch and real- time processing, and learn how to harness tools like Kafka, Airflow, and NiFi to orchestrate seamless data flows. Beyond the technical, the book addresses vital aspects like data quality, governance, and security, offering strategies to ensure data accuracy, lineage, and compliance. From integrating data across APIs, databases, and sensors to leveraging cloud-native architectures for scalability, this guide equips readers with the knowledge to optimize every aspect of their data ecosystems. With practical insights, advanced analytics techniques, and real-world case studies, Data Pioneers delves into performance optimization, resource management, and the future of big data, exploring trends like AI integration and data fabric concepts. Whether you ’ re a seasoned engineer or new to the field, this book provides a roadmap to unlocking the full potential of big data engineering, driving innovation, and achieving sustainable growth in today’s data- driven world.

Learn Apache Airflow

DOWNLOAD
Author : Diego Rodrigues
language : en
Publisher: StudioD21
Release Date : 2025-05-01

Learn Apache Airflow written by Diego Rodrigues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-01 with Business & Economics categories.

LEARN APACHE AIRFLOW Master Data Orchestration with Technical Precision This book is ideal for students, data engineers, analysts, and DevOps professionals who want to master Apache Airflow for orchestrating complex workflows in production environments. You will learn how to configure DAGs, work with operators, integrate external APIs, scale with Celery and Kubernetes, and apply best practices in security and observability. Explore concepts such as XCom, trigger rules, parallelism, remote logging, and DAG versioning, all with a focus on practical application. Includes: • Creation and execution of DAGs with native operators • Integration with REST APIs, databases, and distributed systems • Configuration of Celery and Kubernetes executors for high scalability • Monitoring implementation with Prometheus and Grafana • Automated deployments with Git and CI/CD pipelines • Security strategies with RBAC, encryption, and secret protection • Performance optimization and load balancing across workers By the end, you will be ready to apply Apache Airflow strategically, ensuring reliable automation, scalability, and data governance in corporate projects. airflow, data orchestration, pipelines, devops, ci/cd, monitoring, automation, scalability, big data, data engineering

The Data Science Toolset

DOWNLOAD
Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2025-03-01

The Data Science Toolset written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-01 with Computers categories.

Unlock the ultimate guide to mastering the expansive world of data science with "The Data Science Toolset." Whether you're a curious beginner or a seasoned analyst, this eBook is your gateway to an arsenal of powerful tools and techniques designed to elevate your data analysis skills and transform the way you work with data. Dive into the essential aspects of data tool selection, from understanding your data requirements to conducting thorough cost-benefit analyses. Unleash the potential of Python with in-depth guidance on libraries like Pandas and NumPy, ensuring you can manipulate data with ease. Elevate your visualization game with advanced techniques using Matplotlib, Seaborn, and interactive Plotly plots. Learn to clean, wrangle, and transform data efficiently and explore R's robust ecosystem, from data manipulation and visualization with ggplot2 to sophisticated statistical modeling. Discover how SQL can be your ally in writing efficient queries and handling complex data operations. Automation awaits you as you delve into workflow tools and pipeline building with Apache Airflow and Luigi. Excel doesn't get left behind; unlock its potential with advanced functions, pivot tables, and powerful data transformation using Power Query. Venture into the world of machine learning, understanding algorithms and model deployment with practical tools like Flask and Docker. Time series analysis and NLP techniques open doors to predictive and text data analysis, while big data frameworks like Hadoop and Spark redefine what you can achieve with vast datasets. With a focus on ethics and privacy, this eBook ensures you maintain integrity and compliance throughout your data journey. Finally, sustain your growth by exploring ways to stay current in the field and expand your professional network. "The Data Science Toolset" is more than a book—it's your companion for navigating the ever-evolving landscape of data science, empowering you with the knowledge to succeed in this dynamic domain. Get ready to transform your data insights into impactful decisions.

Data Pipelines With Apache Airflow Second Edition

DOWNLOAD
Author : Julian de Ruiter
language : en
Publisher: Simon and Schuster
Release Date : 2026-02-10

Data Pipelines With Apache Airflow Second Edition written by Julian de Ruiter and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-02-10 with Computers categories.

Data Pipelines with Apache Airflow has empowered thousands of data engineers to build more successful data platforms. This new second edition has been fully revised for Airflow 3 with coverage of all the latest features of Apache Airflow, including the Taskflow API, deferrable operators, and Large Language Model integration. Filled with real-world scenarios and examples, you'll be carefully guided from Airflow novice to expert. Using real-world scenarios and examples, this book teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Part reference and part tutorial, each technique is illustrated with engaging hands-on examples, from training machine learning models for generative AI to optimizing delivery routes. In Data Pipelines with Apache Airflow, Second Edition you'll learn how to: • Master the core concepts of Airflow architecture and workflow design • Schedule data pipelines using the Dataset API and time tables, including complex irregular schedules • Develop custom Airflow components for your specific needs • Implement comprehensive testing strategies for your pipelines • Apply industry best practices for building and maintaining Airflow workflows • Deploy and operate Airflow in production environments • Orchestrate workflows in container-native environments • Build and deploy Machine Learning and Generative AI models using Airflow About the Technology Apache Airflow provides a unified platform for collecting, consolidating, cleaning, and analyzing data. With its easy-to-use UI, powerful scheduling and monitoring features, plug-and-play options, and flexible Python scripting, Airflow makes it easy to implement secure, consistent pipelines for any data or AI task. About the book Data Pipelines with Apache Airflow, Second Edition teaches you how to build, monitor, and maintain effective data workflows. This new edition adds comprehensive coverage of Airflow 3 features, such as event-driven scheduling, dynamic task mapping, DAG versioning, and Airflow’s entirely new UI. The numerous examples address common use cases like data ingestion and transformation and connecting to multiple data sources, along with AI-aware techniques such as building RAG systems. What's inside • Deploying data pipelines as Airflow DAGs • Time and event-based scheduling strategies • Integrating with databases, LLMs, and AI models • Deploying Airflow using Kubernetes About the reader For data engineers, machine learning engineers, DevOps, and sysadmins with intermediate Python skills. About the author Julian de Ruiter, Ismael Cabral, Kris Geusebroek, Daniel van der Ende, and Bas Harenslak are seasoned data engineers and Airflow experts. Table of Contents Part 1 1 Meet Apache Airflow 2 Anatomy of an Airflow DAG 3 Time-based scheduling 4 Asset-aware scheduling 5 Templating tasks using the Airflow context 6 Defining dependencies between tasks Part 2 7 Triggering workflows with external input 8 Communicating with external systems 9 Extending Airflow with custom operators and sensors 10 Testing 11 Running tasks in containers Part 3 12 Best practices 13 Project: Finding the fastest way to get around NYC 14 Project: Keeping family traditions alive with Airflow and generative AI Part 4 15 Operating Airflow in production 16 Securing Airflow 17 Airflow deployment options A Running code samples B Prometheus metric mapping

Python For Data Pipelines

DOWNLOAD
Author : Wolf Blitzer
language : en
Publisher: Independently Published
Release Date : 2025-10-10

Python For Data Pipelines written by Wolf Blitzer and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-10 with Computers categories.

Are your data pipelines slowing you down? Do you want to master Airflow, Dask, and cloud-native ETL like a pro? What if you could build scalable, production-ready data systems that power real-time insights and never break under pressure? In today's data-driven world, the ability to design scalable, automated, and efficient data pipelines separates great engineers from the rest. Python for Data Pipelines: Crafting Scalable ETL Solutions is your complete, hands-on guide to building modern data workflows that can handle anything-from massive batch jobs to real-time analytics across AWS, Google Cloud, and Azure. Whether you're a data engineer, developer, or cloud architect, this book shows you exactly how to move from theory to production using proven frameworks like Apache Airflow and Dask, with deep dives into ETL, ELT, data lakes, and distributed computing. What You'll Learn ✅ Master Apache Airflow - Automate, schedule, and orchestrate complex data workflows with confidence. ✅ Scale with Dask - Process massive datasets in parallel without breaking a sweat. ✅ Go Cloud-Native - Build powerful ETL systems on AWS, GCP, and Azure using Glue, BigQuery, and Data Factory. ✅ Optimize and Monitor - Discover strategies for cost control, fault tolerance, and real-time performance monitoring. ✅ Learn by Doing - Every concept comes with hands-on projects, real-world case studies, and production-ready code. Who This Book Is For Data Engineers who want to build scalable, maintainable pipelines. Python Developers aiming to break into data engineering. Data Scientists seeking to understand how their data is sourced, transformed, and delivered. Cloud Professionals building cost-efficient, automated ETL solutions. Why This Book Stands Out Unlike abstract tutorials, this guide gives you real-world, enterprise-grade examples. You'll see how leading companies in e-commerce, healthcare, and finance solve real data challenges with Python-based pipelines-complete with reusable templates and best practices for production environments. Take Control of Your Data Future If you're ready to design pipelines that scale effortlessly, automate workflows intelligently, and bring true reliability to your data infrastructure - this is the book you've been waiting for.