Managing Data as a Product: Design and build data-product-centered socio-technical architectures

В этом материале разберём тему: data.

As maintenance costs escalate, these platforms lose their ability to provide sustained value over time. Traditional monolithic data platforms struggle with scalability and burden central data teams with excessive cognitive load, leading to challenges in managing technological debt. With two decades of hands-on experience implementing data solutions and his pioneering work in the Open Data Mesh Initiative, Andrea Gioia brings practical insights and proven strategies for transforming how organizations manage their data assets.

In this book, you’ll explore the rationale behind this shift, understand the core features and structure of data products, and learn how to identify, develop, and operate them in a production environment. Managing Data as a Product introduces a modular and distributed approach to data platform development, centered on the concept of data products. The book guides you through designing and implementing an incremental, value-driven strategy for adopting data product-centered architectures, including strategies for securing buy-in from stakeholders. Additionally, it explores data modeling in distributed environments, emphasizing its crucial role in fully leveraging modern generative AI solutions.

By the end of this book, you’ll have gained a comprehensive understanding of product-centric data architecture and the essential steps needed to adopt this modern approach to data management.

What you will learnOvercome the challenges in scaling monolithic data platforms, including cognitive load, tech debt, and maintenance costs

Discover the benefits of adopting a data-as-a-product approach for scalability and sustainability

Navigate the complete data product lifecycle, from inception to decommissioning

Automate data product lifecycle management using a self-serve platform

Implement an incremental, value-driven strategy for transitioning to data-product-centric architectures

Optimize data modeling in distributed environments to enhance GenAI-based use cases

Whether you’re a staff engineer, product manager, or a software engineering leader or executive, you’ll find this book useful. Who this book is forIf you’re an experienced data engineer, data leader, architect, or practitioner committed to reimagining your data architecture and designing one that enables your organization to get the most value from your data in a sustainable and scalable way, this book is for you. Familiarity with basic data engineering principles and practices is assumed.

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