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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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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

Managing the data product portfolio

The data products defined based on the business cases become part of the broader portfolio of data products managed by an organization. The composition and evolution of this portfolio need to be managed in order to maximize value for the organization and minimize associated risks as much as possible. In this section, we will explore some key activities in the process of managing the data product portfolio.

Validating data product proposals

Before a new data product proposal is added to the portfolio, it must be validated. The validation process ensures that the data product complies with the principles and rules governing architecture development. Here are some examples of checks that can be performed at this stage:

  • The data product must specify which domain it belongs to and who owns it.
  • The data product must have a clear value proposition, linked to a specific business case if possible.
  • A source-aligned data product must belong...
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