The Hybrid Data Platform
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Designing And Scaling Cloud Native Data Platforms 2025
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Author : 1.DEVARSH HEMANTBHAI PATEL, 2.DR RICHA MISHRA
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Designing And Scaling Cloud Native Data Platforms 2025 written by 1.DEVARSH HEMANTBHAI PATEL, 2.DR RICHA MISHRA and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In an era defined by unprecedented data growth and ever evolving business demands, traditional data platforms strain under the weight of scale, flexibility, and speed. The advent of cloudy native architectures has transformed how we store, process, and analyze dataenabling organizations to extract real time insights, innovate more rapidly, and deliver resilient services at global scale. Yet with this new promise comes new complexity: distributed storage and computing, microservices based pipelines, streaming event buses, container orchestration, and a bewildering array of open source components. How do we cut through the complexity to design data platforms that are dependable, performant, and maintainable? How do we build systems that grow seamlessly from prototype to production at petabyte scale? This book”Designing and Scaling Cloud Native Data Platforms”was born out of those questions. Drawing on over a decade of hands on experience building large scale systems for leading technology companies, we offer a practical, patterns driven guide to architecting data platforms in the cloud. You will find the foundational principles of cloud native designelasticity, fault isolation, infrastructure as code, and declarative configurationand see how they apply to data challenges such as streaming ingestion, batch processing, data interchange, and real time analytics. Each chapter tackles a different facet of the platform: selecting the right storage and compute primitives; designing event driven data pipelines; ensuring schema evolution and governance; automating deployment, monitoring, and scaling; and securing sensitive data in a zero trust world. We introduce reference architectures and walk through real world exampleswhether it is a clickstream driven analytics pipeline, a multi tenant data lake, or a globally distributed cache for machine learning models. This book is for architects, platform engineers, and data professionals who want to go beyond proof of concepts to build production grade, cloud native platforms that stand the test of scale, complexity, and time. Whether you are embarking on your first cloud migration or leading the next generation of data infrastructure, our aim is to equip you with insights, patterns, and hands on guidance to navigate the modern data landscape. We invite you to explore these pages not as a cookbook of silver bullet solutions, but as a compass for making informed design decisions. May this guide inspire you to craft data platforms that are not only powerful and scalable, but also elegant, resilient, and ready for whatever challenges lie ahead. Authors Devarsh Hemantbhai Patel,Dr Richa Mishra
Architecting Data And Machine Learning Platforms
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Author : Marco Tranquillin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-10-12
Architecting Data And Machine Learning Platforms written by Marco Tranquillin and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-12 with Computers categories.
All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks. Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage. You'll learn how to: Design a modern and secure cloud native or hybrid data analytics and machine learning platform Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities Enable your business to make decisions in real time using streaming pipelines Build an MLOps platform to move to a predictive and prescriptive analytics approach
Building Cloud Data Platforms Solutions
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Author : Anouar BEN ZAHRA
language : en
Publisher: Anouar BEN ZAHRA
Release Date :
Building Cloud Data Platforms Solutions written by Anouar BEN ZAHRA and has been published by Anouar BEN ZAHRA this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
"Building Cloud Data Platforms Solutions: An End-to-End Guide for Designing, Implementing, and Managing Robust Data Solutions in the Cloud" comprehensively covers a wide range of topics related to building data platforms in the cloud. This book provides a deep exploration of the essential concepts, strategies, and best practices involved in designing, implementing, and managing end-to-end data solutions. The book begins by introducing the fundamental principles and benefits of cloud computing, with a specific focus on its impact on data management and analytics. It covers various cloud services and architectures, enabling readers to understand the foundation upon which cloud data platforms are built. Next, the book dives into key considerations for building cloud data solutions, aligning business needs with cloud data strategies, and ensuring scalability, security, and compliance. It explores the process of data ingestion, discussing various techniques for acquiring and ingesting data from different sources into the cloud platform. The book then delves into data storage and management in the cloud. It covers different storage options, such as data lakes and data warehouses, and discusses strategies for organizing and optimizing data storage to facilitate efficient data processing and analytics. It also addresses data governance, data quality, and data integration techniques to ensure data integrity and consistency across the platform. A significant portion of the book is dedicated to data processing and analytics in the cloud. It explores modern data processing frameworks and technologies, such as Apache Spark and serverless computing, and provides practical guidance on implementing scalable and efficient data processing pipelines. The book also covers advanced analytics techniques, including machine learning and AI, and demonstrates how these can be integrated into the data platform to unlock valuable insights. Furthermore, the book addresses an aspects of data platform monitoring, security, and performance optimization. It explores techniques for monitoring data pipelines, ensuring data security, and optimizing performance to meet the demands of real-time data processing and analytics. Throughout the book, real-world examples, case studies, and best practices are provided to illustrate the concepts discussed. This helps readers apply the knowledge gained to their own data platform projects.
Designing Big Data Platforms
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Author : Yusuf Aytas
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-08
Designing Big Data Platforms written by Yusuf Aytas and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-08 with Mathematics categories.
DESIGNING BIG DATA PLATFORMS Provides expert guidance and valuable insights on getting the most out of Big Data systems An array of tools are currently available for managing and processing data—some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security. This real-world manual for Big Data technologies: Provides up-to-date coverage of the tools currently used in Big Data processing and management Offers step-by-step guidance on building a data pipeline, from basic scripting to distributed systems Highlights and explains how data is processed at scale Includes an introduction to the foundation of a modern data platform Designing Big Data Platforms: How to Use, Deploy, and Maintain Big Data Systems is a must-have for all professionals working with Big Data, as well researchers and students in computer science and related fields.
The Hybrid Data Platform
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Author : Dwayne Daniel
language : en
Publisher: Independently Published
Release Date : 2025-09-29
The Hybrid Data Platform written by Dwayne Daniel and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-29 with Computers categories.
The Hybrid Data Platform: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer Building modern data pipelines isn't just about moving information from point A to point B-it's about creating systems that are scalable, governed, and adaptable to the demands of today's enterprises. In a world where data volume, velocity, and variety keep increasing, how do you design architectures that are both efficient and future-ready? This book answers that question by showing how AWS Glue and Kubernetes can be combined to create hybrid data platforms that balance automation with flexibility. Written for data engineers, architects, and technical leaders, it provides a step-by-step framework for architecting cloud-native pipelines that handle batch, streaming, and advanced analytics workloads. Whether you're aiming to improve enterprise reporting, enable machine learning pipelines, or expand into multi-cloud operations, this book gives you the strategies and tools to succeed. What sets this book apart is its practical structure, moving from foundations to real-world implementations. You'll explore: The Evolution of Data Engineering - why hybrid architectures are becoming essential. Foundations of AWS Glue and Kubernetes - core components, architecture, and how they complement each other. Designing Hybrid Pipelines - patterns that integrate serverless workflows with containerized workloads. Building Data Lakes and Handling Mixed Workloads - strategies for batch, streaming, and real-time data. Security, Governance, and Compliance - IAM, RBAC, and regulatory alignment in hybrid environments. Monitoring, Logging, and Optimization - how to ensure reliability, observability, and cost efficiency. Real-World Use Cases and Future-Proofing - enterprise analytics, AI integration, and sustainable scaling. Every chapter blends technical depth with practical insights, supported by extended code snippets, deployment templates, and curated recommendations in the appendix. The result is a resource that doesn't just explain hybrid data platforms-it equips you to build and operate them confidently. If you're a data engineer looking to stay ahead of the curve, or a decision-maker seeking to guide your team toward sustainable cloud-native solutions, this book will show you how to architect hybrid data platforms that scale with your needs. Take the next step toward mastering hybrid cloud data engineering-make this book your guide to building pipelines that deliver both immediate results and long-term value.
Harness The Power Of Big Data The Ibm Big Data Platform
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Author : Paul Zikopoulos
language : en
Publisher: McGraw Hill Professional
Release Date : 2012-10-18
Harness The Power Of Big Data The Ibm Big Data Platform written by Paul Zikopoulos and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-18 with Computers categories.
Boost your Big Data IQ! Gain insight into how to govern and consume IBM’s unique in-motion and at-rest Big Data analytic capabilities Big Data represents a new era of computing—an inflection point of opportunity where data in any format may be explored and utilized for breakthrough insights—whether that data is in-place, in-motion, or at-rest. IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is infusing open source Big Data technologies with IBM innovation that manifest in a platform capable of "changing the game." The four defining characteristics of Big Data—volume, variety, velocity, and veracity—are discussed. You’ll understand how IBM is fully committed to Hadoop and integrating it into the enterprise. Hear about how organizations are taking inventories of their existing Big Data assets, with search capabilities that help organizations discover what they could already know, and extend their reach into new data territories for unprecedented model accuracy and discovery. In this book you will also learn not just about the technologies that make up the IBM Big Data platform, but when to leverage its purpose-built engines for analytics on data in-motion and data at-rest. And you’ll gain an understanding of how and when to govern Big Data, and how IBM’s industry-leading InfoSphere integration and governance portfolio helps you understand, govern, and effectively utilize Big Data. Industry use cases are also included in this practical guide.
Master Competitive Analytics With Oracle Endeca Information Discovery
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Author : Helen Sun
language : en
Publisher: McGraw Hill Professional
Release Date : 2014-09-24
Master Competitive Analytics With Oracle Endeca Information Discovery written by Helen Sun and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-24 with Computers categories.
Oracle Endeca Information Discovery Best Practices Maximize the powerful capabilities of this self-service enterprise data discovery platform. Master Competitive Analytics with Oracle Endeca Information Discovery reveals how to unlock insights from any type of data, regardless of structure. The first part of the book is a complete technical guide to the product's architecture, components, and implementation. The second part presents a comprehensive collection of business analytics use cases in various industries, including financial services, healthcare, research, manufacturing, retail, consumer packaged goods, and public sector. Step-by-step instructions on implementing some of these use cases are included in this Oracle Press book. Install and manage Oracle Endeca Server Design Oracle Endeca Information Discovery Studio visualizations to facilitate user-driven data exploration and discovery Enable enterprise-driven data exploration with Oracle Endeca Information Discovery Integrator Develop and implement a fraud detection and analysis application Build a healthcare correlation application that integrates claims, patient, and operations analysis; partners; clinical research; and remote monitoring Use an enterprise architecture approach to incrementally establish big data and analytical capabilities
Exploration And Implementation Of Wireless Protocol Platforms
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Author : Suet-Fei Li
language : en
Publisher:
Release Date : 2003
Exploration And Implementation Of Wireless Protocol Platforms written by Suet-Fei Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Ced
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Author :
language : en
Publisher:
Release Date : 1996
Ced written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Broadband communication systems categories.
Proceedings
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Author :
language : en
Publisher:
Release Date : 2007
Proceedings written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Integrated circuits categories.