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Konieczny B: Data Engineering Design
Patterns

Data Engineering Design Patterns

Recipes for Solving the Most Common Data Engineering Problems

A big picture analysis of quantitative factor investing combined with practical tools and strategies, including the latest machine learning techniques In The Quantamental Revolution: Factor Investing in the Age of Machine Learning, veteran quantitative investor and strategist, Milind Sharma, delivers a comprehensive discussion of factor investing, risk premia, smart betas, multi-factor models and the deployment of ML ensembles towards monetizing alpha in the hedge fund world. Sharma draws on 30 years of industry and academic experience to bring us up to date on the cutting edge of quantitative factor investing. You'll learn about the basics of Fama-French and obtain a practical blueprint for taming the factor zoo. This book provides a comprehensive factor investing framework designed to improve your investment process informed by an insightful industry perspective and backed up by 1st hand eye witness stories as narrated by the author. The Quantamental Revolution also includes: <ul> <li>A mature and sweeping perspective, simultaneously incorporating industry (insider) insights and academic rigor, not provided by any other reference</li> <li>Novel research backed by live performance leveraging a huge factor library</li> <li>A practical reinvention of buy-side equities using a spanning set of factors and ML enhanced smart betas</li> </ul> Perfect for early-career quantitative investors and analysts, traders, and market data professionals, The Quantamental Revolution is also an essential read for portfolio managers interested in improving their investment processes. The engaging anecdotal vignettes coupled with academic rigor provide the reader with an authentic front row seat to the evolution of Quantamental investing on Wall Street over the past three decades.

Factor Investing in the Age of Machine Learning

The Quantamental Revolution

Transform raw data into business insights Businesses run on data and Microsoft® Power BI is the engine for turning data into insight and decisions. This beginner-friendly guide helps you get started with the Power BI basics. It's also great for power users, covering advanced topics like integrating AI and programming your own functions. This updated edition shows you how to get even more power out of the tool, with enhanced collaboration, customization, and version control. Harness the power of Power BI, the easy way. Inside... <ul> <li>Turn data into business growth</li> <li>Set up Power BI in any business</li> <li>Discover trends in your data</li> <li>Collaborate in real-time</li> <li>Build interactive dashboards</li> <li>Create branded visualizations</li> <li>Use AI for enhanced efficiency</li> <li>Program your own functions</li> </ul>

Microsoft Power BI For Dummies

Every project carries uncertainty. Costs overrun, schedules slip, and revenues disappoint - not because project managers lack skill, but because most risk analyses rely on single-point estimates that conceal the true range of possible outcomes. This book provides a structured framework for project risk management, combines it with rigorous quantitative risk analysis, and shows how artificial intelligence makes both accessible to every practitioner, regardless of budget or technical background. Artificial Intelligence and Risk Analysis in Projects delivers a complete, practitioner-focused framework covering the full project risk management lifecycle - from risk identification and qualitative assessment through quantitative risk analysis, response planning, and monitoring and control. The quantitative core of the book addresses Monte Carlo simulation, probabilistic NPV and IRR appraisal, decision trees, Expected Monetary Value, sensitivity analysis, and the calibration of probability distributions from real project data. A case study running through the book compares two capital investment projects under deterministic and probabilistic analysis, demonstrating concretely how single-point estimates overstate expected returns and conceal the probability of loss - in one case by more than 70%. The AI dimension is integrated throughout rather than treated as a separate topic: readers learn how large language models support risk identification and qualitative analysis, how AI enhances the accuracy of Monte Carlo simulation inputs, how structured prompt engineering directs AI toward specific risk management tasks, and how AI performs as an independent model auditor and stress-testing partner. The book addresses the governance, validation, and accountability structures that responsible AI deployment in project environments requires, and closes by demonstrating Monte Carlo simulation using AI alone - making rigorous probabilistic analysis accessible to practitioners who lack access to commercial simulation software.Written for project risk managers, project controls professionals, and students of project management, this is the first book to unite a structured project risk management framework, rigorous quantitative risk analysis, and applied artificial intelligence in a single integrated treatment. It is both a professional reference and a practical guide - grounded in real case studies, immediately applicable to real project decisions, and positioned at the frontier of where the project risk management profession is heading.

Artificial Intelligence and Risk Analysis in Projects

Easy and effective strategies for using AI chatbots Turn your business into a 24/7 customer service powerhouse with AI chatbots that work around the clock! Perfect for anyone drowning in customer emails or missing sales opportunities while they sleep, AI Chatbots For Dummies explains how to build intelligent chatbots from scratch - no coding required. You'll discover how major companies use chatbots to boost efficiency and customer satisfaction and learn to create your own automated assistants for customer service, lead generation, and marketing campaigns that practically run themselves. Inside ... <ul><li>Build no-code solutions</li><li>Create 24/7 customer support</li><li>Accelerate lead generation</li><li>Convert leads into customers</li><li>Reduce overhead and workload</li><li>Improve customer satisfaction</li><li>Scale your company</li><li>Integrate the newest tools</li></ul>

AI ChatBots For Dummies

Energy, Agriculture and Healthcare are key areas which address the development of the nation. Technology plays a vital role in the development of Energy, Agriculture and Healthcare.

Technologies for Energy, Agriculture, and Healthcare

This book analyzes how human resource experts perceive that robots and evolving technologies will impact leadership behaviors and human resource management in the hospitality industry.As with any new technological innovation, organizations must balance the opportunities afforded by robots with the pressures that are placed on existing organizational processes and strategies. They need to consider not only economic and technical perspectives, but also the user and organizational perspectives when determining the appropriate use and implementation of robots and other technology. Chapters in this collection explore service robots, automation, the Green Collar Revolution, social media, and more in multiple hospitality contexts, including all-inclusive resorts and the industry in Türkiye. Robots and their Impact on Hospitality Leadership is ideal for professionals and leaders in the hospitality industry, as well as students within tourism and hospitality courses.

Robots and their Impact on Hospitality Leadership

Chapman & Hall/Distributed Computing and Intelligent Data Analytics Series

This book explores the transformative potential of artificial intelligence (AI) and data engineering in shaping the future of smart cities. With the rapid growth of urbanisation, cities are facing complex challenges such as efficient resource management, urban mobility, environmental sustainability, and citizen well-being. It offers authoritative insights and perspectives brought together by leading experts to delve into the latest advancements and applications of AI and data engineering in addressing urban challenges.¿ Includes practical insights, case studies and real-world examples of how AI and data engineering are being applied in smart city initiatives¿ Presents the role of AI in enhancing urban infrastructure, optimizing energy consumption, enabling intelligent transportation systems, and empowering citizen participation.¿ Showcases how AI and data engineering can revolutionise urban landscapes and pave the way for sustainable and intelligent cities¿ Discusses the ethical and privacy concerns related to the use of these technologies in cities, highlighting the importance of responsible and sustainable development.¿ Presents an interdisciplinary approach, exploring the intersection of AI and data engineering with fields such as urban planning, transportation, energy and health.The book is primarily aimed at researchers, practitioners, and students in the fields of computer science, engineering and urban planning. It is also relevant to policymakers, government officials, and other professionals involved in the development and implementation of smart city solutions.

AI and Data Engineering for Smart Cities

ICISAS 2025 is the signature research conference of Curtin University Dubai. It brings together leading experts to discuss how innovation, sustainability, and applied sciences can shape the future of business and society.

Integrating Sustainable Technologies with Data-Driven Solutions

The Future of Business and Society

Marketing Technology is the ideal textbook for understanding technology-driven marketing strategy in a digital-first world. This textbook provides upper-level undergraduate and postgraduate students with a comprehensive understanding of how innovation shapes marketing strategy and practice in the modern business environment. Blending theory, strategic models and applied insights, this textbook explores the technologies transforming marketing from: artificial intelligence and machine learning to blockchain, automation and augmented, virtual and mixed realities. Students will learn how to use data and critical thinking to deliver measurable impact and build customer trust in an era of continuous digital evolution. Designed for academic alignment, with key terms, key points, exercises, and reflective questions and real-world application, this textbook includes: 
- Detailed coverage of the historical connection between technology and marketing, big data, neuromarketing, smart devices for enhanced consumer engagement, Internet of Things (IoT) and their role in contemporary marketing strategy
- Frameworks for optimizing campaign performance through analytics, automation and return on investment measurement
- Ethical perspectives are explored in each chapter highlighting responsible and transparent use of marketing technology
- Online lecturer resources include presentation slides Whether studying digital marketing, strategic marketing or marketing management, Marketing Technology by Ediz Edip Akçay, equips students with the expertise and confidence to analyse, apply and innovate with the tools shaping the future of marketing.

Integrating Martech for Transformational Marketing

Marketing Technology

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

The Deep Learning Revolution

Learn more and discover downloadable resources at aiprecipice.com! 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¿overlooked topics in major AI literature, including in¿depth 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

Companies are now moving generative AI projects out of the lab and into production environments. To support these increasingly sophisticated applications, they're turning to advanced practices such as multi-agent architectures and complex code-based frameworks. This practical handbook shows you how to leverage cutting-edge techniques using Microsoft's powerful ecosystem of tools to deploy trustworthy AI systems tailored to your organization's needs. Written for and by AI professionals, Generative AI on Microsoft Azure goes beyond the technical core aspects, examining underlying principles, tools, and practices in depth, from the art of prompt engineering to strategies for fine-tuning models to advanced techniques like retrieval-augmented generation (RAG) and agentic AI. Through real-world case studies and insights from top experts, you'll learn how to harness AI's full potential on Azure, paving the way for groundbreaking solutions and sustainable success in today's AI-driven landscape. <ul> <li>Understand the technical foundations of generative AI and how the technology has evolved over the last few years</li> <li>Implement advanced GenAI applications using services like Microsoft Foundry or Copilot, among others</li> <li>Leverage patterns, tools, frameworks, and platforms to customize AI projects</li> <li>Manage, govern, and secure your AI-enabled systems with responsible AI practices</li> <li>Learn to avoid common pitfalls, future-proof your applications, and more </li> </ul>

From Large Language Models to Advanced Multi-Agent Systems

Generative AI on Microsoft Azure

Data Engineering Design Patterns

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