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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

Product type Paperback

Published in Nov 2024

Publisher Packt

ISBN-13 9781835468531

Length 368 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Data Engineering

Author (1):

Andrea Gioia

View More author details

Table of Contents (18) Chapters

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

Why subscribe?

17. Other Books You May Enjoy

Further reading

For more information on the topics covered in this chapter, please see the following resources:

Context Mapping – DDD-Crew https://github.com/ddd-crew/context-mapping
Building an Event-Driven Data Mesh – Adam Bellemare (2023) https://www.amazon.com/Building-Event-Driven-Data-Mesh-Architectures/dp/1098127609
What is a Composable Business Application? – Massimo Pezzini (2023) https://www.youtube.com/watch?v=_oHqiDWTrAQ&t=1333s
Data Product Descriptor Specification – Open Data Mesh Initiative https://dpds.opendatamesh.org/
Data Product Specification – AgileLab https://github.com/agile-lab-dev/Data-Product-Specification
Open Data Contract Standard – BITOL https://github.com/bitol-io/open-data-contract-standard
Functional Data Engineering — a modern paradigm for batch data processing – Maxime Beauchemin (2018) https://maximebeauchemin.medium.com/functional-data-engineering-a-modern...

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Authors (1)

Andrea Gioia

Andrea Gioia

Andrea Gioia is a partner and CTO at Quantyca, a consulting firm specializing in data management, and co-founder of blindata.io, a SaaS platform for data governance and compliance. With over 20 years of experience, Andrea has led cross-functional teams delivering complex data projects across multiple industries. As CTO, he advises clients on defining and executing their data strategies. Andrea is a frequent speaker and writer, serving as the main organizer of the Data Engineering Italian Meetup and leading the Open Data Mesh Initiative. He is an active DAMA member and has been part of the DAMA Italy Chapter's scientific committee since 2023.

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