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Principles of data fabric : become a data-driven organization by implementing data fabric solutions efficiently /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Mezzetta, Sonia (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing Ltd., 2023.
Edición:1st edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Mezzetta, Sonia,  |e author. 
245 1 0 |a Principles of data fabric :  |b become a data-driven organization by implementing data fabric solutions efficiently /  |c Sonia Mezzetta. 
250 |a 1st edition. 
264 1 |a Birmingham, UK :  |b Packt Publishing Ltd.,  |c 2023. 
300 |a 1 online resource (188 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
500 |a Includes index. 
520 |a 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. 
505 0 |a Cover -- Title Page -- Copyright and Credits -- Dedication -- Contributors -- Table of Contents -- Preface -- 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 
505 8 |a 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 
505 8 |a 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 
505 8 |a 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 
505 8 |a 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 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Data integration (Computer science) 
650 0 |a Big data. 
650 0 |a Database management. 
650 6 |a Intégration de données (Informatique) 
650 6 |a Données volumineuses. 
650 6 |a Bases de données  |x Gestion. 
650 7 |a Big data  |2 fast 
650 7 |a Data integration (Computer science)  |2 fast 
650 7 |a Database management  |2 fast 
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