Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh (Paperback)
暫譯: 解碼數據架構:在現代數據倉庫、數據織物、數據湖屋和數據網格之間的選擇 (平裝本)
Serra, James
- 出版商: O'Reilly
- 出版日期: 2024-03-12
- 定價: $2,800
- 售價: 9.0 折 $2,520
- 語言: 英文
- 頁數: 275
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1098150767
- ISBN-13: 9781098150761
-
相關分類:
大數據 Big-data
立即出貨
買這商品的人也買了...
-
$402遊戲數據分析的藝術 -
Designing with Data|善用數據幫你打造好設計 (Designing with Data: Improving the User Experience with A/B Testing)$580$458 -
基於 CUDA 的 GPU 並行程序開發指南 (GPU Parallel Program Development Using CUDA)$1,074$1,020 -
$2,070Database Internals: A Deep Dive Into How Distributed Data Systems Work (Paperback) -
中臺架構與實現:基於 DDD 和微服務$534$507 -
$402OpenMP 核心技術指南 -
並行計算與高性能計算$834$792 -
高並發系統實戰派:集群、Redis 緩存、海量存儲、Elasticsearch、RocketMQ、微服務、持續集成等$654$621 -
$861系統分析與設計, 9/e -
$2,070Building an Event-Driven Data Mesh: Patterns for Designing & Building Event-Driven Architectures (Paperback) -
DevOps Handbook |打造世界級技術組織的實踐指南, 2/e (中文版) (The Devops Handbook: How to Create World-Class Agility, Reliability, & Security in Technology Organizations, 2/e)$650$487 -
SRE 實踐與開發平台指南:從團隊協作、原則、架構和趨勢掌握全局,做出精準決策$620$483 -
$473數以達理:量化研發管理指南 -
$708現代 C++ 軟件架構:方法與實踐 -
$2,115Automating Data Quality Monitoring: Scaling Beyond Rules with Machine Learning (Paperback) -
$1,568Software Supply Chain Security: Securing the End-To-End Supply Chain for Software, Firmware, and Hardware (Paperback) -
$1,350The Engineering Executive's Primer: Impactful Technical Leadership (Paperback) -
程式設計守則|如何寫出更好的程式碼 (The Rules of Programming: How to Write Better Code)$620$489 -
$354基於近鄰思想和同步模型的聚類算法 -
前端測試指南:策略與實踐$650$507 -
$1,880Defensive Security Handbook: Best Practices for Securing Infrastructure (Paperback) -
C++ 之美:代碼簡潔、安全又跑得快的 30個要訣 (Beautiful C++: 30 Core Guidelines for Writing Clean, Safe, and Fast Code)$654$621 -
無瑕的程式碼 軟體工匠篇:程式設計師必須做到的紀律、標準與倫理 (Clean Craftsmanship: Disciplines, Standards, and Ethics)$720$561 -
軟體設計耦合的平衡之道:建構模組化軟體系統的通用設計原則 (Balancing Coupling in Software Design: Successful Software Architecture in General and Distributed Systems)$650$507 -
深入淺出軟體架構 (Head First Software Architecture)$980$774
Oreilly英文書展|任選2書8折 詳見活動內容 »
-
90折
$2,520Data Engineering for Multimodal AI: Architecting Scalable Systems for Next-Generation AI Applications -
90折
$2,520Data Engineering for Multimodal AI: Architecting Scalable Systems for Next-Generation AI Applications -
90折
$2,592Practical Mlflow for Generative AI on Databricks: Build High-Quality AI Agents from Prompt Design to Production -
90折
$2,457MLOps with Databricks: Machine Learning and Genai Applications End to End -
VIP 95折
An Illustrated Guide to AI Agents: Concepts and Code for Building Agents with Llms, Tools, and Memory (Paperback)$2,780$2,641 -
90折
$2,520Blue Team Handbook: Soc, Siem, and Threat Hunting: Practical Techniques for Security Operations and Threat Hunting Teams -
90折
$1,944Building Agentic Solutions with Microsoft Foundry: Patterns, Workflows, and Best Practices for Intelligent Agents -
90折
$1,917Learning Cybersecurity Fundamentals: A Practical Guide to Essential Cybersecurity Concepts -
VIP 95折
Head First Algorithms and Data Structures: A Learner's Guide to the Foundations of Computing (Paperback)$2,780$2,641 -
90折
$2,484Comptia Linux+ Study Guide: Essential Exam Prep -
90折
$2,520Video Generation with AI: Working with Diffusion Transformers and Multimodal Learning (Paperback) -
90折
$1,890Mapping Experiences: A Complete Guide to Activating Customer-Centered Collaboration 3/e -
90折
$2,520Databricks Certified Generative AI Engineer Associate Study Guide: Generative AI with Databricks -
90折
$2,502Ai-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python -
90折
$2,223Observability Engineering: Achieving Production Excellence, 2/e (Paperback) -
90折
$1,935Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data -
90折
$1,953The C4 Model: Visualizing Software Architecture (Paperback) -
90折
$1,935Learning Cloud Security: Cloud Computing and Security Architecture Essentials -
90折
$2,520Vision Language Models: Building Vlms with Hugging Face (Paperback) -
90折
$2,142High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark 2/e -
90折
$1,944Python for Excel: A Modern Environment for Automation and Data Analysis -
90折
$1,440Managing AI Projects: Drive Innovation and Successfully Navigate the Full AI Project Lifecycle (Paperback) -
90折
$2,520AI-Ready Data Blueprints: From Raw Data to Ai-Driven Innovation (Paperback) -
90折
$1,917Certified Kubernetes Application Developer (Ckad) Study Guide: In-Depth Guidance and Practice (Paperback) -
90折
$2,484Large Language Models: The Hard Parts: Open Source AI Solutions for Common Pitfalls (Paperback)
相關主題
商品描述
Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of each architecture to help data professionals understand its pros and cons.
In the process, James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You'll learn what data lakehouses can help you achieve, and how to distinguish data mesh hype from reality. Best of all, you'll be able to determine the most appropriate data architecture for your needs. By reading this book, you'll:
- Gain a working understanding of several data architectures
- Know the pros and cons of each approach
- Distinguish data architecture theory from the reality
- Learn to pick the best architecture for your use case
- Understand the differences between data warehouses and data lakes
- Learn common data architecture concepts to help you build better solutions
- Alleviate confusion by clearly defining each data architecture
- Know what architectures to use for each cloud provider
商品描述(中文翻譯)
資料織布(data fabric)、資料湖屋(data lakehouse)和資料網格(data mesh)最近成為現代資料倉儲的可行替代方案。這些新架構具有明確的優勢,但同時也伴隨著許多誇大其詞和混淆。本書提供了每種架構的導覽,幫助資料專業人士理解其優缺點。
在此過程中,微軟的大數據與資料倉儲解決方案架構師 James Serra 會探討常見的資料架構概念,包括資料倉儲如何演變以配合資料湖的特性。您將學習資料湖屋能幫助您達成的目標,以及如何區分資料網格的誇大與現實。最重要的是,您將能夠確定最適合您需求的資料架構。閱讀本書後,您將能:
- 獲得對幾種資料架構的實用理解
- 知道每種方法的優缺點
- 區分資料架構理論與現實
- 學會為您的使用案例選擇最佳架構
- 理解資料倉儲與資料湖之間的差異
- 學習常見的資料架構概念,以幫助您構建更好的解決方案
- 通過明確定義每種資料架構來減輕混淆
- 知道對於每個雲服務提供商應使用哪些架構