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Konieczny B: Data Engineering Design
Patterns

Data Engineering Design Patterns

Recipes for Solving the Most Common Data Engineering Problems

'Kiko Llaneras is one of the most consistently interesting data journalists to have emerged in the last decade' John Burn-Murdoch, Chief data reporter, Financial Times It's almost impossible to feel confident we've made the right choice when we are constantly faced with conflicting data. From choosing the right school for our children to understanding major social and political events, making informed decisions can feel overwhelming. In a world overflowing with data, it is more important than ever to decipher what the numbers tell us. Drawing on years of work interpreting and explaining data about almost anything, renowned data journalist Kiko Llaneras offers practical tools and shortcuts to help you understand the numbers and make better decisions using a quantitative lens. Through a series of compelling examples, he reveals some of the surprising insights that a data-driven perspective can offer such as: <ul><li>What caused the Chernobyl disaster</li><li>How Barack Obama made decisions and slept so peacefully during his presidency</li><li>Why so many footballers are born in January</li></ul> An essential guide for decoding the complexities of our modern world, Think Clearly will transform the way you view and use data in every aspect of your life.

Eight Simple Rules to Succeed in the Data Age

Think Clearly

An easy-to-follow guide to demystifying Agentic AI, the next step in the evolution of artificial intelligence Agentic AI is the next big leap in artificial intelligence. Agentic systems don't just respond to commands. They set goals, make decisions, and take initiative without direct human interaction. Sound like a lot to wrap your head around? Fortunately Agentic AI For Dummies is here to help you gain understanding of this advancing technology. Written by the author of ChatGPT For Dummies and Generative AI For Dummies, this easy-to-understand tech guide helps you take your first steps into Agentic AI. Get insight into the technologies driving Agentic AI, a road map for shifting from legacy systems to Agentic systems, and a tour of real-world use cases for Agentic AI. This books arms you with an understanding to make better decisions about how and when to use Agentic AI technologies. Inside the book: <ul> <li>Discussions of the technological foundations of agentic AI</li> <li>Explorations of the wide variety of applications of the AI agents, including in scientific research, innovation, business operations, healthcare, and more</li> <li>Insightful examinations of the ethical considerations and hurdles you'll need to navigate when it's time to deploy agentic AI in your company</li> </ul> Perfect for business owners, entrepreneurs, managers, executives, professionals and team leaders in the private sector, Agentic AI For Dummies is a hands-on toolkit and strategy guide for using autonomous AI solutions to solve hard problems in your organization.

Agentic AI For Dummies

Drawing from her experience at Google and Meta, Dr. Marily Nika delivers the definitive guide for product managers building AI and GenAI powered products. Packed with smart strategies, actionable tools, and real-world examples, this book breaks down the complex world of AI agents and generative AI products into a playbook for driving innovation to help product leaders bridge the gap between niche AI and GenAI technologies and user pain points. Whether you're already leading product teams or are an aspiring product manager, and regardless of your prior knowledge with AI, this guide will empower you to confidently navigate every stage of the AI product lifecycle. <ul> <li>Confidently manage AI product development with tools, frameworks, strategic insights, and real-world examples from Google, Meta, OpenAI, and more</li> <li>Lead product orgs to solve real problems via agentic AI and GenAI capabilities</li> <li>Gain AI Awareness and technical fluency to work with AI models, LLMs, and the algorithms that power them; get cross-functional alignment; make strategic trade-offs; and set OKRs</li>
</ul>

The Essential Guide to AI and GenAI Product Management

Building AI-Powered Products

This book offers a comprehensive and application-oriented exploration of Artificial Intelligence and Natural Language Processing (NLP), addressing both foundational principles and modern, data-driven methodologies. It is designed to equip readers with a deep understanding of how intelligent systems learn from data, interpret human language, and support automated decision-making across real-world contexts.Natural Language Processing for Business and Organizations: Research and Innovation cover key areas such as machine learning, deep learning, text representation, language modeling, information extraction, sentiment analysis, and AI-driven analytics, while also discussing system design considerations for deploying NLP solutions at scale. Through carefully structured chapters, the book integrates theoretical insights with practical examples, case studies, and applied workflows, enabling readers to translate algorithms and models into effective AI applications. Written by a team of academic researchers and industry practitioners, the book emphasizes responsible and value-driven AI, including ethical considerations, data quality, and model evaluation.This book is written for advanced undergraduate and postgraduate students, researchers, and professionals seeking to build, evaluate, and apply AI and NLP systems in academic, enterprise, and societal domains.

Research and Innovation

Natural Language Processing for Business and Organizations

Geopolitics, Vulnerabilities, Sustainability, Activisms

Data Centre Entanglements

This book fills a significant gap by providing a leadership guide to balance innovation and safety. With the rapid business transformation underway to leverage artificial intelligence (AI), executives must allocate substantial investments in governance, corporate purpose, and risk management tailored to their organization's strategic goals. The stakes are high, and very few organizations are generating positive returns on their investments. As a result, leaders must reevaluate their strategies, focusing on maximizing benefits while curtailing unnecessary costs. This book emphasizes the importance of carefully integrating humans into AI processes and introduces a robust leadership framework that prioritizes innovation without compromising safety. Diverse industry examples offer rich insights into pathways for striking a balance between advancing AI capabilities and mitigating potential risks.This book equips leaders with the tools to navigate the complexities of AI responsibly. It sheds light on often¿verlooked topics in major AI literature, including in¿epth discussions on strategic scenarios, risks and controls, legal frameworks, and effective measurement systems. Offering a wealth of strategic and operational insights from credible sources, this authoritative resource is indispensable for senior executives aiming to design, develop, and implement successful AI initiatives within their organizations.

An Executive Guide to Balancing AI Innovation and Safety

The AI Precipice

Recursions

A Media Theory of Machine Learning

Errant Intelligence

'Engaging, insightful, panoramic' Mustafa Suleyman, CEO of Microsoft AI &amp; Cofounder of DeepMind 'An eye-opening exploration of a revolution unfolding before our eyes' New York Journal of Books Stunning advances in digital technology have introduced a new wave of human-like AI systems. Chatbots like ChatGPT, Claude, and Gemini are already reshaping economies, challenge democracies, and reshaping society in unpredictable ways. And soon, these AI systems could make autonomous decisions on their users' behalf, transforming everything we do. Understanding how they work is crucial. Can AI systems think, know, and understand?Could they manipulate or deceive you, and if so, what might they make you do? Whose interests do they represent? When will they be able to move beyond words and take action in the real world? Neuroscientist and AI researcher Christopher Summerfield explores these questions, charting AI's evolution from early ideas in the seventeenth century to today's deep neural networks. His book is the most accessible, up-to-date, and authoritative exploration of this radical technology. With an understanding of AI's inner workings, we can address the existential question of our age: can we look forward to a technological utopia, or are we writing ourselves out of history? 'As a leading authority...Summerfield is perfectly situated to explore the meaning and implications of these machines that are so uncannily like - and unlike - ourselves' Brian Christian, co-author of Algorithms to Live by 'You might choose to be alarmed, excited, or indifferent to LLMs, but you should read Chris's book before you decide' Mike Woolridge, author of The Road to Conscious Machines

How AI Learned to Talk and What It Means

These Strange New Minds

A roadmap for business leaders to unlock the full potential of data, machine learning, and artificial intelligenceMore than 90 percent of businesses surveyed say they want to capitalize on data--but two-thirds admit to feeling stuck. What these leaders do not realize is that to succeed at becoming a data-driven business requires developing a nuanced understanding of why data holds such transformative power, what a data-inspired culture looks like, and how to get there.Data Inspired shows that the secret isn't to be more data-driven--it is to become data-inspired. This book reveals the crucial strategic distinction between using data to optimize existing operations and using them as a catalyst for deep transformation and innovation. Wernicke argues that this success hinges less on technology and more on reshaping an organization's culture and decision-making habits. And with the book's proven principles, real-world examples, and comprehensive toolbox of methods for building a culture of evidence-based inquiry, readers will learn that success means far more than just adding more data to a business: it is about creating a thoroughly data-inspired organization with innovative work methods, new structures, and unmatched efficiency.Data Inspired will help business leaders, managers, and data professionals move beyond incremental improvements to achieve lasting, powerful change.

Building an Organizational Culture of Inquiry for Lasting Transformation

Data Inspired

Taylor and Francis Proceedings in Environmental Science and Engineering

This proceedings compilation presents groundbreaking contemporary research on digital transformation and its profound impact on industries, institutions, and societies. Through 67 peer-reviewed papers, this volume takes a multidisciplinary approach and delves into technological change, sustainability, and innovation in the digital era.The contributions span artificial intelligence applications, sustainable business practices, fintech and digital finance, technology adoption, innovation and entrepreneurship, human resource transformation, governance, and digital education systems. Several studies examine AI-enabled decision-making, automation, data-driven strategy, and emerging digital infrastructures, while others explore sustainability transitions, inclusive development, financial inclusion, and policy frameworks in technology-mediated environments. The collection also features empirical analyses, conceptual models, technical innovations, and sector-specific case studies from diverse regional contexts. Together, these papers document current research directions, practical implementations, and strategic responses shaping organizations and economiesThis book is intended for researchers, scholars, and professionals engaged in digital transformation, innovation, and technology management. It serves as a reference for academics, industry leaders, policymakers, and research institutions seeking current evidence, interdisciplinary perspectives, and emerging insights into technological change and its organisational, economic, and societal implications.

Sustainable Innovations in Management in the Digital Transformation Era

A complete guide to deep neural networks – the technology behind AI – covering fundamental and advanced techniques to apply machine learning in real-world scenarios. Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.

Deep Learning Crash Course

The book presents real-life applications of Data Science and Big Data for Sustainable Development Goals. It includes a list of case studies from different regions across India. The book uses both structured and unstructured data like numeric data, textual data, video/image data, etc., across the various chapters for the analysis. It further delves into various data science techniques, starting from data collection on the ground in the unavailability of data to a dashboard, reporting, unsupervised methods like clustering, artificial intelligence, machine learning and deep learning, search or information retrieval, time series forecasting, optimisation, etc.¿ Showcase data science decision-making processes, driving innovation, and solving complex problems in real-case scenarios from across sectors like finance, healthcare, and e-commerce.¿ The SDGs provide a framework for societal development and well-being for all; the data science and big data interventions in this book are aligned towards mapping the various SDG goals.¿ Most of the data science use cases and initiatives projects covered in this book have been implemented by the central or state governments across different states of India.¿ Shows how data science intervention can transform the social sector, potentially driving positive change and addressing critical societal challenges.¿ Explained the fundamentals of data science theories, including concepts like classification, classification, regression, predictive analytics, optimisation, artificial intelligence, deep learning, time series forecasting, etc. for readers of different disciplines.It serves as a valuable reference for graduate students, researchers, and scholars seeking to deepen their knowledge and engage with real life applications of Data Science. This will also serve as a valuable resource for government officers and policy practitioners, providing a range of cases on the use of data-based methods for improving governance and policy making.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC BY-NC-ND)] 4.0 license funded by by the Great Lakes Institute of Management, Gurgaon Campus, Delhi NCR, India.

Indian Case Studies

Data Science for Sustainable Development Goals

Data Engineering Design Patterns

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