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Položka č.:
103032991
Scalable Data Architecture with Java: Build efficient enterprise-grade data architecting solutions using Java
Položka č.:
103032991
CZK 1077
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By the end of this book, you'll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.
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Detaily produktu
- Orchestrate data architecting solutions using Java and related technologies to evaluate, recommend and present the most suitable solution to leadership and clientsKey FeaturesLearn how to adapt to the ever-evolving data architecture technology landscapeUnderstand how to choose the best suited technology, platform, and architecture to realize effective business valueImplement effective data security and governance principlesBook DescriptionJava architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data.This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert.You'll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you'll understand how to architect a batch and real-time data processing pipeline. You'll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you'll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics.By the end of this book, you'll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.What you will learnAnalyze and use the best data architecture patterns for problemsUnderstand when and how to choose Java tools for a data architectureBuild batch and real-time data engineering solutions using JavaDiscover how to apply security and governance to a solutionMeasure performance, publish benchmarks, and optimize solutionsEvaluate, choose, and present the best architectural alternativesUnderstand how to publish Data as a Service using GraphQL and a REST APIWho this book is forData architects, aspiring data architects, Java developers and anyone who wants to develop or optimize scalable data architecture solutions using Java will find this book useful. A basic understanding of data architecture and Java programming is required to get the best from this book.Table of ContentsBasics of Modern Data ArchitectureData Storage and DatabasesIdentifying the Right Data PlatformETL Data Load - A Batch-Based Solution to Ingest Data in a Data WarehouseArchitecting a Batch Processing PipelineArchitecting a Real-Time Processing PipelineCore Architectural Design PatternsEnabling Data Security and GovernanceExposing MongoDB Data as a ServiceFederated and Scalable DaaS with GraphQLMeasuring Performance and Benchmarking Your ApplicationsEvaluating, Recommending, and Presenting Your Solutions
| Publisher | Packt Publishing |
| Publication date | September 30, 2022 |
| Edition | 1st |
| Language | English |
| File size | 40.2 MB |
| Screen Reader | Supported |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 382 pages |
| ISBN-13 | 978-1801072083 |
| Page Flip | Enabled |
| Item Weight | 0.5 lbs (230 grams) |
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Scalable Data Architecture with Java: Build efficient enterprise-grade data architecting solutions using Java
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Java Editorial Review
### Editorial Review This comprehensive guide on data architecture and engineering presents a structured approach for both seasoned Java developers and aspiring data architects. The book navigates through fundamental concepts such as data types, storage formats, and databases while emphasizing practical applications related to real-world scenarios. Each section builds upon the previous one, guiding the reader through the complete data workflow from data ingestion to deployment and maintenance. Readers commend the book for its in-depth exploration of the entire data pipeline, highlighting its focus on popular software and tools like AWS, Kafka, and MongoDB, which are critical in today's tech landscape. This pragmatic approach makes it easier for developers to seek assistance and apply their knowledge effectively. The use-case driven methodology adds further value by illustrating real-world applications of theoretical concepts. The author’s clear writing style and step-by-step guidance provide a solid foundation for understanding complex topics such as data governance and performance tuning. However, some reviewers suggest areas for improvement, indicating a desire for expanded discussion on parsing complex data, advanced garbage collection algorithms, and critical theoretical frameworks like the CAP theorem. Overall, this book is seen as an essential resource for those looking to enhance their understanding of data architecture within the context of Java, making it a valuable addition to any technical library. ### Pros and Cons **
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7 hodnocení zákazníků
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Klady
- Comprehensive coverage of the entire data workflow.
- Focus on widely used software/tools, facilitating problem-solving and community support.
- Use-case based learning enhances practical understanding.
- Clear explanation of core data engineering concepts and design patterns.
- Well-structured and step-by-step guidance for implementing data solutions.
Nevýhody
- Could benefit from more details on data parsing, especially for complex formats.
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Služby a výhody
- Learn to build enterprise-grade data architectures using Java.
- Understand the technology landscape and choose the best solutions.
- Implement data security and governance effectively.
- Explore both batch and real-time data processing architectures.
- Evaluate and present architectural solutions with performance metrics.
- Targeted at data architects, Java developers, and those optimizing data architecture.
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