Learn Data Mesh
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Data Mesh In Action
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Author : Jacek Majchrzak
language : en
Publisher: Simon and Schuster
Release Date : 2023-02-14
Data Mesh In Action written by Jacek Majchrzak 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 2023-02-14 with Business & Economics categories.
Revolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. Data Mesh in Action reveals how this groundbreaking architecture looks for both startups and large enterprises. You won't need any new technology--this book shows you how to start implementing a data mesh with flexible processes and organizational change. You'll explore both an extended case study and real-world examples. As you go, you'll be expertly guided through discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-product system. Plus, dozens of workshop techniques for both in-person and remote meetings help you onboard colleagues and drive a successful transition.
Learn Data Mesh
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Author : Diego Rodrigues
language : en
Publisher: Studiod21
Release Date : 2025-10-29
Learn Data Mesh 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 2025-10-29 with Business & Economics categories.
LEARN DATA MESH Master Distributed Governance and Modern Data Architecture This book is recommended for students and professionals seeking practical mastery in Data Mesh, distributed data architecture, multi-cloud integration, governance, and data pipeline automation in modern corporate environments. The content covers everything from the fundamentals of Data Mesh to its implementation with leading frameworks such as AWS Lake Formation, Azure Synapse, Databricks, Google BigQuery, Kafka, Apache Spark, Kubernetes, Airflow, dbt, Snowflake, Terraform, Prometheus, Grafana, and ELK Stack. Explore strategies for data decentralization, domain-oriented architecture, data product management, CI/CD pipeline automation, multidisciplinary team integration, monitoring, security, and scalability for high-performance data environments. Learn to build robust solutions, integrate heterogeneous sources, implement data governance practices, S3, IAM, deployment automation, observability, and compliance with LGPD/GDPR. You will learn: * Essential concepts and pillars of Data Mesh: domains, data products, interoperability, and self-service platforms * Reference architecture with AWS, Azure, Google Cloud, Databricks, Snowflake, and Kubernetes * Orchestration of data pipelines with Apache Airflow, dbt, Spark, Kafka, and Terraform * Implementation of monitoring, observability, and automation with Prometheus, Grafana, and ELK Stack * Data integration in multi-cloud, container, and edge computing environments * Best practices in security, authentication, IAM, governance, and compliance * Deployment automation, backup, versioning, and troubleshooting in corporate environments By the end, you will be able to apply Data Mesh to create scalable, secure, auditable, and business-oriented data platforms, optimizing analytical and operational workflows in data-driven companies of any size. data mesh data architecture AWS Azure Google Cloud Databricks Snowflake pipelines Apache Airflow dbt Spark Kafka Kubernetes automation, CI/CD, data products observability grafana ELK LGPD GDPR security IAM integration backup governance compliance
Data Mesh In Action
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Author : Jacek Majchrzak
language : en
Publisher: Simon and Schuster
Release Date : 2023-03-21
Data Mesh In Action written by Jacek Majchrzak 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 2023-03-21 with Computers categories.
Revolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. In Data Mesh in Action you will learn how to: Implement a data mesh in your organization Turn data into a data product Move from your current data architecture to a data mesh Identify data domains, and decompose an organization into smaller, manageable domains Set up the central governance and local governance levels over data Balance responsibilities between the two levels of governance Establish a platform that allows efficient connection of distributed data products and automated governance Data Mesh in Action reveals how this groundbreaking architecture looks for both small startups and large enterprises. You won’t need any new technology—this book shows you how to start implementing a data mesh with flexible processes and organizational change. You’ll explore both an extended case study and multiple real-world examples. As you go, you’ll be expertly guided through discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-product system. Plus, dozens of workshop techniques for both in-person and remote meetings help you onboard colleagues and drive a successful transition. About the technology Business increasingly relies on efficiently storing and accessing large volumes of data. The data mesh is a new way to decentralize data management that radically improves security and discoverability. A well-designed data mesh simplifies self-service data consumption and reduces the bottlenecks created by monolithic data architectures. About the book Data Mesh in Action teaches you pragmatic ways to decentralize your data and organize it into an effective data mesh. You’ll start by building a minimum viable data product, which you’ll expand into a self-service data platform, chapter-by-chapter. You’ll love the book’s unique “sliders” that adjust the mesh to meet your specific needs. You’ll also learn processes and leadership techniques that will change the way you and your colleagues think about data. What's inside Decompose an organization into manageable domains Turn data into a data product Set up central and local governance levels Build a fit-for-purpose data platform Improve management, initiation, and support techniques About the reader For data professionals. Requires no specific programming stack or data platform. About the author Jacek Majchrzak is a hands-on lead data architect. Dr. Sven Balnojan manages data products and teams. Dr. Marian Siwiak is a data scientist and a management consultant for IT, scientific, and technical projects. Table of Contents PART 1 FOUNDATIONS 1 The what and why of the data mesh 2 Is a data mesh right for you? 3 Kickstart your data mesh MVP in a month PART 2 THE FOUR PRINCIPLES IN PRACTICE 4 Domain ownership 5 Data as a product 6 Federated computational governance 7 The self-serve data platform PART 3 INFRASTRUCTURE AND TECHNICAL ARCHITECTURE 8 Comparing self-serve data platforms 9 Solution architecture design
Data Mesh
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Author : Zhamak Dehghani
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-03-08
Data Mesh written by Zhamak Dehghani 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 2022-03-08 with Computers categories.
We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, author Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale. Dehghani guides practitioners, architects, technical leaders, and decision makers on their journey from traditional big data architecture to a distributed and multidimensional approach to analytical data management. Data mesh treats data as a product, considers domains as a primary concern, applies platform thinking to create self-serve data infrastructure, and introduces a federated computational model of data governance. Get a complete introduction to data mesh principles and its constituents Design a data mesh architecture Guide a data mesh strategy and execution Navigate organizational design to a decentralized data ownership model Move beyond traditional data warehouses and lakes to a distributed data mesh
Engineering Data Mesh In Azure Cloud
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Author : Aniruddha Deswandikar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29
Engineering Data Mesh In Azure Cloud written by Aniruddha Deswandikar 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 2024-03-29 with Computers categories.
Overcome data mesh adoption challenges using the cloud-scale analytics framework and make your data analytics landscape agile and efficient by using standard architecture patterns for diverse analytical workloads Key Features Delve into core data mesh concepts and apply them to real-world situations Safely reassess and redesign your framework for seamless data mesh integration Conquer practical challenges, from domain organization to building data contracts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDecentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help. The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud. The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI). By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.What you will learn Build a strategy to implement a data mesh in Azure Cloud Plan your data mesh journey to build a collaborative analytics platform Address challenges in designing, building, and managing data contracts Get to grips with monitoring and governing a data mesh Understand how to build a self-service portal for analytics Design and implement a secure data mesh architecture Resolve practical challenges related to data mesh adoption Who this book is for This book is for chief data officers and data architects of large and medium-size organizations who are struggling to maintain silos of data and analytics projects. Data architects and data engineers looking to understand data mesh and how it can help their organizations democratize data and analytics will also benefit from this book. Prior knowledge of managing centralized analytical systems, as well as experience with building data lakes, data warehouses, data pipelines, data integrations, and transformations is needed to get the most out of this book.
Data Mesh
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Author : Alex Campbell
language : en
Publisher: Mjpublishing4972
Release Date : 2024-10-05
Data Mesh written by Alex Campbell and has been published by Mjpublishing4972 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-05 with Computers categories.
Gain a broader understanding of Data Mesh and logical architecture. Have you ever asked yourself why you need to learn about Data Mesh? What is their use in our daily life? Have you ever wondered what the logical architecture is for a data mesh? Your data is like a mesh. It's everywhere, and it's connected. You have data on your servers, your networks, and your clients. And it's not just one kind of data-it's all different types that need to be organized and made sense of to be useful. The problem is that these data types are often stored in different places with different formats, making them hard to access and use together. This book will help you understand the root causes of this problem and how to solve them using today's most advanced techniques in data management. It is a book about the structure of a data mesh. It defines data mesh, how it works, and why you might want to use it. The main purpose of this book is to help you understand what exactly a data mesh is, and how it works on a fundamental level. It will also teach you about the principles of a data mesh, as well as its logical architecture. This book was written for anyone who wants to learn more about this technology. Whether you're an engineer or developer working with a data mesh, someone who's just curious about how they work, or an entrepreneur looking at ways to improve your company's efficiency or productivity-this book will help you understand what these technologies are all about! In this book, you will: Learn the Data Mesh, its state, and its future Learn about the practical uses of Data Mesh Get background knowledge about Data Mesh with concrete examples Master Domain Ownership Principle Discover the principle behind the self-serve data platform Learn about the federated computational government principle Discover the point of inflection Master the logical architecture Data Mesh is not just a framework; it's an approach to data modeling that emphasizes simplicity, clarity, and scalability. This book will teach you how to use Data Mesh to build a logical architecture that scales.
Big Data Machine And Deep Learning
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Author : Rajesh Kumar Mishra
language : en
Publisher: GRIN Verlag
Release Date : 2025-04-11
Big Data Machine And Deep Learning written by Rajesh Kumar Mishra and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-11 with Computers categories.
Scientific Study from the year 2025 in the subject Computer Sciences - Artificial Intelligence, , language: English, abstract: In recent times, developments in artificial intelligence (AI) and machine learning (ML) have propelled improvements in systems and control engineering. We exist in a time of extensive data, where AI and ML can evaluate large volumes of information instantly to enhance efficiency and precision in decisions based on data. In control engineering, for instance, AI algorithms can anticipate system behaviors and autonomously modify controls to enhance performance for better efficiency and dependability. ML models, with their ability to learn, consistently enhance their predictions and choices as they handle additional data, enabling systems to dynamically adjust to evolving environments and operational circumstances. This swift adjustment enhances the functions of current systems and enables the creation of groundbreaking solutions, like self-driving cars and intelligent power grids, which were previously deemed unfeasible. The rapid expansion of digital data has propelled significant advancements in Big Data analytics, Machine Learning, and Deep Learning. These technologies are increasingly integrated across industries, facilitating automated decision-making, predictive modeling, and advanced pattern recognition. This chapter provides an in-depth review of recent progress in these domains, emphasizing breakthroughs in scalable data processing frameworks, cloud and edge computing, AutoML, explainable AI, transformer architectures, self-supervised learning, and generative models. Furthermore, it explores key applications in healthcare, finance, and autonomous systems, along with challenges such as data privacy, ethical concerns, and computational constraints. The discussion concludes with future directions, highlighting the potential of federated learning, neuromorphic computing, and novel algorithmic improvements to further expand AI's impact across disciplines.
Data Fabric And Data Mesh Approaches With Ai
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Author : Eberhard Hechler
language : en
Publisher: Apress
Release Date : 2023-04-08
Data Fabric And Data Mesh Approaches With Ai written by Eberhard Hechler and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-08 with Computers categories.
Understand modern data fabric and data mesh concepts using AI-based self-service data discovery and delivery capabilities, a range of intelligent data integration styles, and automated unified data governance—all designed to deliver "data as a product" within hybrid cloud landscapes. This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses artificial intelligence (AI) and machine learning (ML) for automated metadata management and self-service data discovery and consumption. You will learn how data fabric and data mesh relate to other concepts such as data DataOps, MLOps, AIDevOps, and more. Many examples are included to demonstrate how to modernize the consumption of data to enable a shopping-for-data (data as a product) experience. By the end of this book, you will understand the data fabric concept and architecture as it relates to themes such as automated unified data governance and compliance, enterprise information architecture, AI and hybrid cloud landscapes, and intelligent cataloging and metadata management. What You Will Learn Discover best practices and methods to successfully implement a data fabric architecture and data mesh solution Understand key data fabric capabilities, e.g., self-service data discovery, intelligent data integration techniques, intelligent cataloging and metadata management, and trustworthy AI Recognize the importance of data fabric to accelerate digital transformation and democratize data access Dive into important data fabric topics, addressing current data fabric challenges Conceive data fabric and data mesh concepts holistically within an enterprise context Become acquainted with the business benefits of data fabric and data mesh Who This Book Is For Anyone who is interested in deploying modern data fabric architectures and data mesh solutions within an enterprise, including IT and business leaders, data governance and data office professionals, data stewards and engineers, data scientists, and information and data architects. Readers should have a basic understanding of enterprise information architecture.
Implementing Data Mesh
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Author : Jean-Georges Perrin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-09-04
Implementing Data Mesh written by Jean-Georges Perrin 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 2024-09-04 with Computers categories.
As data continues to grow and become more complex, organizations seek innovative solutions to manage their data effectively. Data mesh is one solution that provides a new approach to managing data in complex organizations. This practical guide offers step-by-step guidance on how to implement data mesh in your organization. In this book, Jean-Georges Perrin and Eric Broda focus on the key components of data mesh and provide practical advice supported by code. Data engineers, architects, and analysts will explore a simple and intuitive process for identifying key data mesh components and data products. You'll learn a consistent set of interfaces and access methods that make data products easy to consume. This approach ensures that your data products are easily accessible and the data mesh ecosystem is easy to navigate. This book helps you: Identify, define, and build data products that interoperate within an enterprise data mesh Build a data mesh fabric that binds data products together Build and deploy data products in a data mesh Establish the organizational structure to operate data products, data platforms, and data fabric Learn an innovative architecture that brings data products and data fabric together into the data mesh About the authors: Jean-Georges "JG" Perrin is a technology leader focusing on building innovative and modern data platforms. Eric Broda is a technology executive, practitioner, and founder of a boutique consulting firm that helps global enterprises realize value from data.
Machine Learning
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Author : Lorenza Saitta
language : en
Publisher: Morgan Kaufmann Publishers
Release Date : 1996
Machine Learning written by Lorenza Saitta and has been published by Morgan Kaufmann Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.