Demystifying Big Data Analytics for Industries and Smart Societies
Data Analytics in Finance
Data Analytics in Finance covers the methods and application of data analytics in all major areas of finance, including buy-side investments, sell-side investment banking, corporate finance, consumer finance, financial services, real estate, insurance, and commercial banking. It explains statistical inference of big data, financial modeling, machine learning, database querying, data engineering, data visualization, and risk analysis. Emphasizing financial data analytics practices with a solution-oriented purpose, it is a "one-stop-shop" of all the major data analytics aspects for each major finance area.The book paints a comprehensive picture of the data analytics process including: Statistical inference of big data Financial modeling Machine learning and AI Database querying Data engineering Data visualization Risk analysis. Each chapter is crafted to provide complete guidance for many subject areas including investments, fraud detection, and consumption finance. Avoiding data analytics methods widely available elsewhere, the book focuses on providing data analytics methods specifically applied to key areas of finance. Written as a roadmap for researchers, practitioners, and students to master data analytics instruments in finance, the book also provides a collection of indispensable resources for the readers' reference. Offering the knowledge and tools necessary to thrive in a data-driven financial landscape, this book enables readers to deepen their understanding of investments, develop new approaches to risk management, and apply data analytics to finance.
From Numbers to Narratives that Transform Businesses
This book shows the reader how to transform cold numbers into captivating narratives that drive business success. Master the art and science of data storytelling, blend logic with creativity, and turn insights into action. Learn to craft stunning visuals, navigate data-driven decisions, and infuse your data with key principles for maximum impact. This book is your roadmap to turning data from mere information into a powerful catalyst for transformation.
Process Mining Workshops
This book constitutes the revised accepted papers of several workshops which were held in conjunction with the 6th International Conference on Process Mining, ICPM 2024, held in Lyngby, Denmark, during October 2024. The 56 revised full papers presented in this book were carefully reviewed and selected from 126 submissions. The papers presented in this volume stem from the following workshops: - 9th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) - 3rd International Workshop on Education Meets Process Mining (EduPM) - 3rd International Workshop on Collaboration Mining for Distributed Systems (CoMinDS) - 5th International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) - 5th International Workshop on Event Data and Behavioral Analytics (EdbA) - 7th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) - 1st International Workshop on Empirical Research in Process Mining (ERPM) - 1st International Workshop on Generative Artificial Intelligence for Process Mining (GenAI4PM) - 4th International Workshop on Stream Management & Analytics for Process Mining (SMA4PM) - 1st International Workshop on Process Mining for Sustainability (PM4S).
Corpus-Based Studies in Specialized Discourses
This book illustrates the complex ways language operates within specific professional and academic contexts. Through a series of meticulously conducted corpus-based studies, the volume explores the unique linguistic features and rhetorical strategies that characterize specialized discourses across various fields, including medicine, engineering, and the humanities. It examines key aspects such as metadiscourse markers, rhetorical structures of research articles, and the customization of vocabulary tools to enhance language learning and professional communication. By revealing patterns and trends that traditional methods might overlook, this collection offers valuable insights for scholars, educators, and practitioners, making it an essential resource for understanding and improving communication withinspecialized domains.
Fundamentals of Software Architecture
Salary surveys worldwide regularly place software architect in the top 10 best jobs, yet no real guide exists to help developers become architects. Until now. This updated edition provides a comprehensive overview of software architecture's many aspects, with five new chapters covering the latest insights from the field. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming architecture, governance, data, generative AI, team topologies, and many other topics. Mark Richards and Neal Ford--hands-on practitioners who have taught software architecture classes professionally for years--focus on architecture principles that apply across all technology stacks. You'll explore software architecture in a modern light, taking into account all the innovations of the past decade. This book examines: Architecture styles and patterns: Microservices, modular monoliths, microkernels, layered architectures, and many more Components: Identification, coupling, cohesion, partitioning, and granularity Soft skills: Effective team management, collaboration, business engagement models, negotiation, presentations, and more Modernity: Engineering practices and operational approaches that have changed radically in the past few years, including cloud considerations and generative AI Architecture as an engineering discipline: Repeatable results, metrics, and concrete valuations that add rigor to software architecture
Big Data and Artificial Intelligence
This book constitutes the proceedings of the 12th International Conference on Big Data and Artificial Intelligence, BDA 2024, held in Hyderabad, India, during December 17-20, 2024. The 16 full papers and 12 short papers presented here were carefully reviewed and selected from 106 submissions. These papers have been categorized under the following topical sections: Image Classification; Graph Analytics; Big Data Analytics; Applications; Data Science; Health-Care Analytics; eLearning; Prediction and Forecasting.
Speak Data
This is no ordinary data science book. Speak Data is the first pop nonfiction book to explore the definition of data and its impacts on our daily lives. Insightful ideas and colorful data illustrations by award-winning information designer Giorgia Lupi guide you from one observation and revelation to the next. "Data is almost anything, because almost anything can get recorded. But it's kind of a magical thing--potentially one of the most powerful things humans have ever done." --James Clear, author of Atomic Habits Today we are told that data is everywhere, from the smartphones in our pockets to the satellites in space. But what is data, really? What role does it play in our lives? And why should anyone care? Through inspiring illustrations and a fresh, accessible approach, Speak Data invites us to see data differently--not just as numbers on a screen or tick marks in a chart, but as a language to help us better understand each other and the world around us. Seventeen thought-provoking conversations with leaders in business, tech, medicine, psychology, health, art, and more explore the human side of data, unpacking its powerful ability to divulge patterns, tell stories, stir emotion, and illuminate complexity. While often stereotyped as abstract or intimidating, here data is revealed as something far different: personal, nuanced, and above all, human made. Featuring: Tech pioneer John Maeda on the value of data visualization during global emergencies. Marketing legend Seth Godin on how to use data to get people to really care about climate change. Museum curator Paola Antonelli on whether data is art. Atomic Habits author James Clear on the ways data can (and can't) describe human identity. AI data artist Refik Anadol on how big datasets can dream. And many more. In this uniquely interdisciplinary study, authors Giorgia Lupi and Phillip Cox present data as a vocabulary that anyone can use and that anyone can understand. If we learn to truly "speak data," we can open up new worlds of meaning for ourselves and everything around us. ESTABLISHED AUTHORITY: Giorgia Lupi is an award-winning information designer whose work is part of the permanent collection of the Museum of Modern Art. She has twice been named to the Wallpaper* USA 400 list of the people shaping creative America and recently became a Fellow of the Royal Society of Art and a National Geographic explorer. A visual OpEd she published in the New York Times in 2023 was a stunning reflection on her experience of long Covid, and her TED Talk on her humanistic approach to data has more than one million views. Her belief is that data has the capacity to make us all more human--advancing our intelligence, engagement, and delight. KALEIDESCOPE OF PERSPECTIVES: Five chapters tackle human-centered topics of data and identity, communications, health, technology, and creativity, exploring what data is today and what it might mean for our collective future. The scientists, artists, writers, researchers, and activists interviewed include James Clear, Adam Grant, Andy Marra, Seth Godin, Bernadette Woods Placky, Nico Muhly, Kate Crawford, and Sougwen Chung. Perfect for: Anyone interested in data science and data visualization Graphic design students and professionals Educators and librarians seeking an instructive and accessible resource on data Readers of modern culture and popular science books Fans of Giorgia Lupi's artwork, TED Talk, and books, including Dear Data and Observe, Collect, Draw!
Business Analytics with Python
Data-driven decision-making is a fundamental component of business success. Use this textbook to learn the core knowledge and techniques for analyzing business data with Python programming.Business Analytics with Python assumes no prior knowledge or experience in computer science, presenting the technical aspects of the subject in an accessible, introductory way for students on business courses. It features chapters on linear regression, neural networks and cluster analysis, with a running case study that enables students to apply their knowledge. Students will also benefit from real-life examples to show how business analysis has been used for such tasks as customer churn prediction, credit card fraud detection and sales forecasting. This book presents a holistic approach to business analytics: in addition to Python, it covers mathematical and statistical concepts, essential machine learning methods and their applications. Business Analytics with Python comes complete with practical exercises and activities, learning objectives and chapter summaries as well as self-test quizzes. It is supported by online resources that include lecturer PowerPoint slides, study guides, sample code and datasets and interactive worksheets. This textbook is ideal for students taking upper level undergraduate and postgraduate modules on analytics as part of their business, management or finance degrees.
Sentiment Analysis Unveiled
This book is a comprehensive exploration into the realm of sentiment analysis. From deciphering customer sentiments for businesses to understanding public opinions on social media or predicting market trends, the applications are multifaceted and impactful.Sentiment Analysis Unveiled: Techniques, Applications, and Innovations is more than just algorithms and models; it's about unraveling the emotions, opinions, and perceptions encapsulated within the vast sea of textual data. This book explores topics from opinion mining, social media analysis, deep learning, security concerns, and healthcare systems, and it also delves into the ethical and legal implications of sentiment analysis. Through practical examples, case studies, and discussions on cutting-edge innovations, the editors aim is to provide a holistic view that empowers you to navigate this field confidently. It involves the analysis of user-generated content, deciphering sentiments expressed on platforms like Twitter and Facebook, and provides valuable insights into public opinion, brand perception, and emerging trends in the digital landscape.This book is intended for professionals, researchers, and scientists in the field of artificial intelligence and sentiments analysis; it will serve as a valuable resource for both beginners and experienced professionals in the field.
Multilingual Entity Linking
This book focuses on Entity Discovery and Linking (EDL), which is the problem of identifying concepts and entities, disambiguating them, and grounding them to one or more knowledge bases (KBs). The authors first provide background on the topic and emphasize why it is a crucial step toward understanding natural language text. As most of the content on the internet is not in English, the book also discusses cross-lingual EDL. The authors present the challenges associated with EDL problems and explain the existing solutions. The book covers the core challenges that apply to all EDL problems, as well as the additional challenges associated with cross-lingual EDL problems. The authors also survey relevant research papers, highlight recent trends, and identify areas for future research.
Natural Language Understanding in Conversational AI with Deep Learning
Natural Language Analytics with Generative Large-Language Models
This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the data science pipeline to generate actionable insights. The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure. Key topics include interpretant, mindset and cultural analysis, emphasizing the use of LLMs to derive soft data--qualitative information crucial for nuanced decision-making. The text also outlines the technical aspects of LLMs, including their architecture, token embeddings, and the differences between encoder-based and decoder-based models. By providing a case study and practical examples, the authors show how LLMs can be used to meet various analytical needs, making this book a valuable resource for anyone looking to integrate advanced natural language processing techniques into their data analysis workflows.
Computational Intelligence in Communications and Business Analytics
This three-volume set CCIS 2366-2368 constitutes the refereed proceedings of the 6th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2024, held in Patna, India, during January 23-25, 2024. The 82 full papers presented in this volume were carefully reviewed and selected from 249 submissions. Together, these papers showcase cutting-edge research in the fields of computational intelligence and business analytics, covering a broad range of topics.
