Principles of Data Fabric: Become a data-driven organization by implementing Data Fabric solutions efficiently
- Length: 188 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2023-04-06
- ISBN-10: 1804615226
- ISBN-13: 9781804615225
- Sales Rank: #0 (See Top 100 Books)
Apply Data Fabric solutions to automate Data Integration, Data Sharing, and Data Protection across disparate data sources using different data management styles.
Purchase of the print or Kindle book includes a free PDF eBook
Key Features
- Learn to design Data Fabric architecture effectively with your choice of tool
- Build and use a Data Fabric solution using DataOps and Data Mesh frameworks
- Find out how to build Data Integration, Data Governance, and Self-Service analytics architecture
Book Description
Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered.
The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You’ll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you’ll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles.
By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution.
What you will learn
- Understand the core components of Data Fabric solutions
- Combine Data Fabric with Data Mesh and DataOps frameworks
- Implement distributed data management and regulatory compliance using Data Fabric
- Manage and enforce Data Governance with active metadata using Data Fabric
- Explore industry best practices for effectively implementing a Data Fabric solution
Who this book is for
If you are a data engineer, data architect, or business analyst who wants to learn all about implementing Data Fabric architecture, then this is the book for you. This book will also benefit senior data professionals such as chief data officers looking to integrate Data Fabric architecture into the broader ecosystem.
Principles of Data Fabric Contributors About the author About the reviewers Preface Who this book is for What this book covers To get the most out of this book Conventions used Get in touch Share Your Thoughts Download a free PDF copy of this book Part 1: The Building Blocks Chapter 1: Introducing Data Fabric What is Data Fabric? What Data Fabric is What Data Fabric is not Why is Data Fabric important? Drawbacks of centralized data management Decentralized data management Building Data Fabric architecture Data Fabric building blocks Data Fabric principles The four Vs Data Governance Knowledge layer Data Integration Self-Service Operational Data Governance models Summary Chapter 2: Show Me the Business Value Digital transformation Data monetization Revenue Cost savings Data Fabric’s value proposition Trusting your decisions with governed data Creating a unified view of your data with intelligent Data Integration Gaining a competitive advantage with Self-Service Data Fabric for large, medium, and small enterprises Large enterprise organizations Small and medium-sized businesses Summary Part 2: Complementary Data Management Approaches and Strategies Chapter 3: Choosing between Data Fabric and Data Mesh Introducing Data Mesh Domain ownership Data as a product Self-Serve data platform Federated computational governance Comparing Data Fabric and Data Mesh Objectives Data Fabric and Data Mesh’s friendship How Data Fabric supports a federated-based organization How Data Fabric manages data as a product Self-Service data platform via a Data Fabric and Data Mesh architecture Federated computational governance with Data Fabric Summary Chapter 4: Introducing DataOps What is DataOps? DataOps’ principles The evolution of DataOps DataOps’ dimensions MLOps and AIOps depend on DataOps DataOps’ value From traditional Data Quality to data observability Data Fabric with DataOps Develop Orchestrate Test Deploy Monitor Summary Chapter 5: Building a Data Strategy Why create a data strategy? A data maturity framework A data maturity assessment Creating a data strategy Topics in a data strategy document Creating a data strategy document Data strategy implementation Summary Part 3: Designing and Realizing Data Fabric Architecture Chapter 6: Designing a Data Fabric Architecture Introduction to enterprise architecture Types of enterprise architecture Data Fabric principles Data Fabric architecture principles Data Fabric architecture layers Data Governance Data Integration Self-Service Summary Chapter 7: Designing Data Governance Data Governance architecture Metadata-driven architecture EDA Metadata as a service Metadata collection Metadata integration Metadata-based events The Data Governance layer Active metadata Life cycle governance Operational models The Data Fabric’s governance applied The Create phase The Ingest phase The Integrate phase The Consume phase The Archive and Destroy phase Summary Chapter 8: Designing Data Integration and Self-Service DataOps-based architecture Data Integration layer Data management Development workflow Self-Service layer Data democratization Data consumption Data journey in a Data Fabric architecture Phase 1 – Create phase in the Data Integration layer Phases 2 and 3 – Ingest and Integrate phases in the Data Integration layer Phase 4 – Consume phase in the Self-Service layer Phase 5 – Archive and Destroy phase Data Fabric reference architecture Data Fabric architecture highlights Summary Chapter 9: Realizing a Data Fabric Technical Architecture Technical Data Fabric architecture Data Fabric tools Vendor and open source tools Use cases Distributed data management and sharing via Data Mesh Regulatory compliance Data Mesh multi-plane requirements Multi-plane architecture Data Mesh assumptions Data Fabric with Data Mesh reference architecture Reference architecture explained Federated operational model Summary Chapter 10: Industry Best Practices Top 16 best practices Data strategy best practices Best practice 1 Best practice 2 Best practice 3 Best practice 4 Data architecture best practices Best practice 5 Best practice 6 Best practice 7 Best practice 8 Best practice 9 Data Integration and Self-Service best practices Best practice 10 Best practice 11 Best practice 12 Data Governance best practices Best practice 13 Best practice 14 Best practice 15 Summary Index Why subscribe? Other Books You May Enjoy Packt is searching for authors like you Share Your Thoughts Download a free PDF copy of this book
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