Managing Data as a Product
Design and build data-product-centered socio-technical architectures
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Learn everything you need to know to manage data as a product and shift toward a more modular and decentralized socio-technical data architecture to deliver business value in an incremental, measurable, and sustainable way Key Features: - Leverage data-as-product to unlock the modular platform potential and fix flaws in traditional monolithic architectures - Learn how to identify, implement, and operate data products throughout their life cycle - Design and execute a forward-thinking strategy to turn your data products into organizational assets - Purchase of the print or Kindle book includes ...
Learn everything you need to know to manage data as a product and shift toward a more modular and decentralized socio-technical data architecture to deliver business value in an incremental, measurable, and sustainable way Key Features: - Leverage data-as-product to unlock the modular platform potential and fix flaws in traditional monolithic architectures - Learn how to identify, implement, and operate data products throughout their life cycle - Design and execute a forward-thinking strategy to turn your data products into organizational assets - Purchase of the print or Kindle book includes a free PDF eBook Book Description: Traditional monolithic data platforms struggle with scalability and burden central data teams with excessive cognitive load, leading to challenges in managing technological debt. As maintenance costs escalate, these platforms lose their ability to provide sustained value over time. 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. Managing Data as a Product introduces a modular and distributed approach to data platform development, centered on the concept of data products. 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. 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 Learn: - Overcome 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 Who this book is for: If 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. Whether you're a staff engineer, product manager, or a software engineering leader or executive, you'll find this book useful. Familiarity with basic data engineering principles and practices is assumed. Table of Contents - From Data as a Byproduct to Data as a Product - Data Products - Data Product-Centered Architectures - Identifying Data Products and Prioritizing Developments - Designing and Implementing Data Products - Operating Data Products in Production - Automating Data Product Lifecycle Management (N.B. Please use the Read Sample option to see further chapters)
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