Synopsis
Transform your organization's data infrastructure with this comprehensive guide to modern data engineering. Written by industry veterans with decades of experience at Fortune 500 companies, this practical handbook bridges the gap between theoretical concepts and real-world implementation.Discover how to build robust, scalable data pipelines using Python - from ingesting raw data to delivering actionable insights. Through hands-on examples and proven architectural patterns, you'll learn to leverage cutting-edge tools like Apache Airflow, Spark, and cloud services to create production-grade data systems.What Sets This Book Apart:
- Complete coverage of modern data engineering, from fundamentals to advanced topics
- Real-world case studies from Netflix, Uber, and other tech giants
- Step-by-step tutorials for building enterprise-grade data pipelines
- Cloud-native architectures using AWS, Google Cloud, and Azure
- Best practices for scalability, monitoring, and security
- Latest trends in real-time processing, machine learning pipelines, and DataOps
- Data engineers looking to level up their skills
- Software engineers transitioning to data roles
- Data scientists who want to understand pipeline architecture
- Engineering managers building data teams
- Students and professionals seeking practical data engineering skills
- Design and implement production-ready data pipelines
- Build scalable ETL workflows using modern tools
- Deploy and monitor cloud-based data solutions
- Optimize performance of big data systems
- Implement data governance and security best practices
"synopsis" may belong to another edition of this title.
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Data Engineering with Python: Building Pipelines and Managing Data
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Paperback. Condition: new. Paperback. Transform your organization's data infrastructure with this comprehensive guide to modern data engineering. Written by industry veterans with decades of experience at Fortune 500 companies, this practical handbook bridges the gap between theoretical concepts and real-world implementation.Discover how to build robust, scalable data pipelines using Python - from ingesting raw data to delivering actionable insights. Through hands-on examples and proven architectural patterns, you'll learn to leverage cutting-edge tools like Apache Airflow, Spark, and cloud services to create production-grade data systems.What Sets This Book Apart: Complete coverage of modern data engineering, from fundamentals to advanced topicsReal-world case studies from Netflix, Uber, and other tech giantsStep-by-step tutorials for building enterprise-grade data pipelinesCloud-native architectures using AWS, Google Cloud, and AzureBest practices for scalability, monitoring, and securityLatest trends in real-time processing, machine learning pipelines, and DataOpsPerfect for: Data engineers looking to level up their skillsSoftware engineers transitioning to data rolesData scientists who want to understand pipeline architectureEngineering managers building data teamsStudents and professionals seeking practical data engineering skillsBy the end of this book, you'll be able to: Design and implement production-ready data pipelinesBuild scalable ETL workflows using modern toolsDeploy and monitor cloud-based data solutionsOptimize performance of big data systemsImplement data governance and security best practicesDon't miss this opportunity to master the skills that top companies are desperately seeking. Whether you're just starting your data engineering journey or looking to stay ahead of the curve, this book is your definitive guide to building world-class data infrastructure. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798303770584
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Paperback. Condition: new. Paperback. Transform your organization's data infrastructure with this comprehensive guide to modern data engineering. Written by industry veterans with decades of experience at Fortune 500 companies, this practical handbook bridges the gap between theoretical concepts and real-world implementation.Discover how to build robust, scalable data pipelines using Python - from ingesting raw data to delivering actionable insights. Through hands-on examples and proven architectural patterns, you'll learn to leverage cutting-edge tools like Apache Airflow, Spark, and cloud services to create production-grade data systems.What Sets This Book Apart: Complete coverage of modern data engineering, from fundamentals to advanced topicsReal-world case studies from Netflix, Uber, and other tech giantsStep-by-step tutorials for building enterprise-grade data pipelinesCloud-native architectures using AWS, Google Cloud, and AzureBest practices for scalability, monitoring, and securityLatest trends in real-time processing, machine learning pipelines, and DataOpsPerfect for: Data engineers looking to level up their skillsSoftware engineers transitioning to data rolesData scientists who want to understand pipeline architectureEngineering managers building data teamsStudents and professionals seeking practical data engineering skillsBy the end of this book, you'll be able to: Design and implement production-ready data pipelinesBuild scalable ETL workflows using modern toolsDeploy and monitor cloud-based data solutionsOptimize performance of big data systemsImplement data governance and security best practicesDon't miss this opportunity to master the skills that top companies are desperately seeking. Whether you're just starting your data engineering journey or looking to stay ahead of the curve, this book is your definitive guide to building world-class data infrastructure. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798303770584
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