Intelligent Product Management In The Era Of Data Democratization A Bi Centric Approach 2025
Download Intelligent Product Management In The Era Of Data Democratization A Bi Centric Approach 2025 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Intelligent Product Management In The Era Of Data Democratization A Bi Centric Approach 2025 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Intelligent Product Management in the Era of Data Democratization: A BI-Centric Approach 2025
Author: AUTHOR-1: SHIREESHA GORGILLI, AUTHOR-2: PROF DR PUNIT GOEL
language: en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date:
PREFACE In the evolving landscape of digital product management, data is no longer a support tool—it is the strategic core. Today’s product leaders are expected not just to build delightful features, but to make rapid, high-stakes decisions informed by real-time data, predictive insights, and collaborative intelligence. The rise of business intelligence (BI) and data democratization has shifted the way organizations think, operate, and scale. This book, “Intelligent Product Management in the Era of Data Democratization: A BI-Centric Approach—serves as a comprehensive guide to this transformation. Whether you’re a product manager navigating cross-functional dynamics, a data engineer embedding predictive analytics into product pipelines, or a business leader scaling governance framework, this book offers the tools, case studies, and frameworks to help you thrive in a BI-enabled world. Each chapter explores a foundational pillar of intelligent product management—from building a data-driven culture and integrating BI across lifecycles, to architecting intelligent metrics systems and deploying automation at scale. Chapter 1 introduces the foundational principles of data democratization, setting the stage for product teams to unlock data fluency and equitable access across roles. Chapter 2 emphasizes cultural transformation, where leadership plays a pivotal role in nurturing a decision-intelligent environment. Chapter 3 dives deep into the BI technology stack, guiding readers through platforms, pipelines, and self-service frameworks essential for modern data operations. Chapters 4 through 6 explore the integration of BI into daily product workflows, visualization best practices, and advanced analytics paradigms—highlighting both centralized and distributed models of control. Chapter 7 ventures into a specialized application of predictive intelligence: battery diagnostics—showing how machine learning revolutionizes lifecycle forecasting and anomaly detection in energy systems. As organizations move from insight to action, Chapters 8 to 10 illustrate the power of collaboration, automation, and role-based governance in driving excellence at scale. These sections provide detailed blueprints for aligning products, engineering, and data teams around shared metrics and objectives, while also reducing operational friction through embedded intelligence and automated experimentation. Finally, Chapter 11 synthesizes the book’s themes through a future-facing lens: designing an intelligent metrics architecture that scales with your product’s complexity and growth. It champions metric thinking not just as a measurement practice, but as a product design principle rooted in continuous learning and impact. This book is designed to be practical yet forward-looking, informed by real-world examples from high-growth companies, backed by research, and structured to serve both new and experienced professionals. In a world where decisions are product features, our aim is to equip you with the mindset and tools to lead boldly with intelligence, empathy, and data. Authors
Human- Centric Integration of Next-Generation Data Science and Blockchain Technology
Human- Centric Integration of Next Generation Data Science and Blockchain Technology: Advancing Society 5.0 Paradigms focuses on the current technological landscape, addressing the evolving integration of data science and blockchain within the context of Society 5.0. This comprehensive resource explains the convergences between data science, blockchain, and the human-centric vision of Society 5.0, while also filling the gap in understanding and navigating this transformative intersection with recent shifts towards more decentralized and data-driven paradigms.The book introduces the concept of Society 5.0, examining the historical context, and outlines the evolving technological landscape shaping our interconnected future. It discusses the fundamental principles of data science, from data collection and preprocessing to exploratory data analysis and explains the transformative impact of data science and blockchain across industries such as healthcare, finance, education, and transportation. This book is essential to understanding and shaping the future of technology and society from decentralized solutions to predictive analytics/ emerging technologies. - Addresses the evolving integration of data science and blockchain within the context of Society 5.0 - Introduces the basic architecture and taxonomy of blockchain technology - Explores the future urban lives under the concept of "Society 5.0", characterized by the key phrases of data-driven society and knowledge-intensive society - Offers a firm foundation and understanding of recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management
Big Data in Practice
The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter