Self Service Bi A Roadmap For Empowered Analytics 2025
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Self-Service BI: A Roadmap for Empowered Analytics 2025
Author: AUTHOR: 1- LAXMI VANAM, AUTHOR: 2 - PROF DR. PUNIT GOEL
language: en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date:
PREFACE In an era where data is often lauded as the new oil, the true differentiator is not merely its abundance but our ability to transform raw information into actionable insights—quickly, confidently, and at scale. Self-Service BI: A Roadmap for Empowered Analytics charts a comprehensive course for organizations and individuals aiming to democratize data, break down technical barriers, and embed analytics into every decision-making process. Drawing on the latest innovations in real-time and streaming analytics, AI-driven augmentation, embedded machine learning, and collaborative workflows, this volume presents a cohesive narrative of how self-service BI has evolved and where it is headed. Every chapter in this book builds upon extensive research, case studies, and emerging best practices. We explore the foundational principles of empowering non-technical users—from well-governed data catalogs and intuitive visual query builders to guide tutorials that foster data literacy. We delve into the architectural underpinnings that make real-time dashboards possible, demonstrating how event-streaming platforms like Kafka and Flink underpin near-instant updates and proactive alerting. We then examine the seamless integration of AI and AutoML directly within BI interfaces—where forecasting, anomaly detection, and clustering happen alongside everyday chart creation. Further chapters illuminate augmented analytics and natural-language querying, which liberate users from complex syntax by allowing them to speak or type questions in plain English. We unpack the rise of social BI—commenting, tagging, and co-authoring features that foster alignment across distributed teams. Embedded and mobile-first BI sections reveal offline caching, responsive design, and API-driven integrations ensure that analytics travel with the user, whether in a CRM, ERP, or bespoke portal. Advanced visualization techniques—AR/VR overlays and generative AI–powered narratives—offer a glimpse into immersive, next-generation experiences. Amidst these innovations, we never lose sight of governance, security, and ethical imperatives. Robust role-based access controls, row- and column-level security, encryption, and automated policy enforcement ensure that empowerment never comes at the cost of compliance or data integrity. Finally, we look ahead to autonomous decisioning agents—reinforcement-learning systems that not only surface insights but execute decisions and refine strategies autonomously Whether you are a data analyst, an executive leading digital transformation, an IT architect, or a budding citizen data scientist, this book offers both the conceptual framework, and the practical guidance needed to navigate the dynamic landscape of self-service BI. May this roadmap empower you to foster a truly data-driven culture where every stakeholder can glean insights, make informed choices, and drive sustained innovation. Authors Laxmi Vanam Prof. Dr. Punit Goel
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
The Self-Service Data Roadmap
Author: Sandeep Uttamchandani
language: en
Publisher: O'Reilly Media
Release Date: 2020-09-10
Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast enough to keep up with the growing amounts of data to transform. What’s the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work. Build a self-service portal to support data discovery, quality, lineage, and governance Select the best approach for each self-service capability using open source cloud technologies Tailor self-service for the people, processes, and technology maturity of your data platform Implement capabilities to democratize data and reduce time to insight Scale your self-service portal to support a large number of users within your organization