Мне всегда нравился продуктовый подход в аналитике. При таком подходе легче донести ценность до бизнеса и удобней измерять эффективность аналитического решения. Сегодня увидел новую книгу - Managing Data as a Product: A comprehensive guide to designing and building data product-centered socio-technical architectures Я уже давно подписан на автора в LinkedIn и мне нравится его специализация и подход. Про книгу: 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. 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 also guides you through the design and implementation of 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 importance in fully leveraging modern generative AI solutions. Upon completing the book, you’ll have gained a comprehensive understanding of product-centric data architecture and the necessary steps to begin adopting this modern approach to data management. What you will learn - Recognize 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 - Gain insights into managing the 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 - Master data modeling in distributed environments to enhance GenAI-based use cases