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Managing Data as a Product

You're reading from   Managing Data as a Product Design and build data-product-centered socio-technical architectures

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835468531
Length 368 pages
Edition 1st Edition
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Author (1):
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Andrea Gioia Andrea Gioia
Author Profile Icon Andrea Gioia
Andrea Gioia
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1: Data Products and the Power of Modular Architectures
2. Chapter 1: From Data as a Byproduct to Data as a Product FREE CHAPTER 3. Chapter 2: Data Products 4. Chapter 3: Data Product-Centered Architectures 5. Part 2: Managing the Data Product Lifecycle
6. Chapter 4: Identifying Data Products and Prioritizing Developments 7. Chapter 5: Designing and Implementing Data Products 8. Chapter 6: Operating Data Products in Production 9. Chapter 7: Automating Data Product Lifecycle Management 10. Part 3: Designing a Successful Data Product Strategy
11. Chapter 8: Moving through the Adoption Journey 12. Chapter 9: Team Topologies and Data Ownership at Scale 13. Chapter 10: Distributed Data Modeling 14. Chapter 11: Building an AI-Ready Information Architecture 15. Chapter 12: Bringing It All Together 16. Index 17. Other Books You May Enjoy

Building an enterprise knowledge graph

So far, we have seen how to define and build an enterprise ontology. Now, let’s explore how to connect it to the developed data products in order to create an enterprise knowledge graph that can represent the entire information architecture in one unified model.

Knowledge Graph Architectures

A knowledge graph is created when the conceptual model, represented by one or more interconnected ontologies, is linked to data that instantiates the concepts within the model. There are three main types of knowledge graph architectures, based on how and when the connections between concepts and data are established (Figure 11.14).

Figure 11.14 – Knowledge Graph Architectures

Figure 11.14 – Knowledge Graph Architectures

The first two architectures shown in the figure are examples of materialized knowledge graphs. In these graphs, the data that represent various business concepts are directly included as concepts within the ontology. For example, if the...

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