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The Data Model Resource Book
by Len SilverstonA quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful First Edition, while adding a companion volume to take care of more specific requirements of different businesses. Each volume is accompanied by a CD-ROM, which is sold separately. Each CD-ROM provides powerful design templates discussed in the books in a ready-to-use electronic format, allowing companies and individuals to develop the databases they need at a fraction of the cost and a third of the time it would take to build them from scratch. Updating the data models from the First Edition CD-ROM, this resource allows database developers to quickly load a core set of data models and customize them to support a wide range of business functions.
The Data Preparation Journey: Finding Your Way with R (Chapman & Hall/CRC Data Science Series)
by Martin Hugh MonkmanThe Data Preparation Journey: Finding Your Way With R introduces the principles of data preparation within in a systematic approach that follows a typical data science or statistical workflow. With that context, readers will work through practical solutions to resolving problems in data using the statistical and data science programming language R. These solutions include examples of complex real-world data, adding greater context and exposing the reader to greater technical challenges. This book focuses on the Import to Tidy to Transform steps. It demonstrates how “Visualise” is an important part of Exploratory Data Analysis, a strategy for identifying potential problems with the data prior to cleaning.This book is designed for readers with a working knowledge of data manipulation functions in R or other programming languages. It is suitable for academics for whom analyzing data is crucial, businesses who make decisions based on the insights gleaned from collecting data from customer interactions, and public servants who use data to inform policy and program decisions. The principles and practices described within The Data Preparation Journey apply regardless of the context.Key Features: Includes R package containing the code and data sets used in the book Comprehensive examples of data preparation from a variety of disciplines Defines the key principles of data preparation, from access to publication
The Data Protection Officer: Profession, Rules, and Role
by Paul LambertThe EU's General Data Protection Regulation created the position of corporate Data Protection Officer (DPO), who is empowered to ensure the organization is compliant with all aspects of the new data protection regime. Organizations must now appoint and designate a DPO. The specific definitions and building blocks of the data protection regime are enhanced by the new General Data Protection Regulation and therefore the DPO will be very active in passing the message and requirements of the new data protection regime throughout the organization. This book explains the roles and responsiblies of the DPO, as well as highlights the potential cost of getting data protection wrong.
The Data Science Framework: A View from the EDISON Project
by Juan J. Cuadrado-Gallego Yuri DemchenkoThis edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader.The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models.The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines.
The Data Science Handbook
by Field CadyPractical, accessible guide to becoming a data scientist, updated to include the latest advances in data science and related fields. Becoming a data scientist is hard. The job focuses on mathematical tools, but also demands fluency with software engineering, understanding of a business situation, and deep understanding of the data itself. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. The focus of The Data Science Handbook is on practical applications and the ability to solve real problems, rather than theoretical formalisms that are rarely needed in practice. Among its key points are: An emphasis on software engineering and coding skills, which play a significant role in most real data science problems.Extensive sample code, detailed discussions of important libraries, and a solid grounding in core concepts from computer science (computer architecture, runtime complexity, and programming paradigms).A broad overview of important mathematical tools, including classical techniques in statistics, stochastic modeling, regression, numerical optimization, and more.Extensive tips about the practical realities of working as a data scientist, including understanding related jobs functions, project life cycles, and the varying roles of data science in an organization.Exactly the right amount of theory. A solid conceptual foundation is required for fitting the right model to a business problem, understanding a tool’s limitations, and reasoning about discoveries. Data science is a quickly evolving field, and this 2nd edition has been updated to reflect the latest developments, including the revolution in AI that has come from Large Language Models and the growth of ML Engineering as its own discipline. Much of data science has become a skillset that anybody can have, making this book not only for aspiring data scientists, but also for professionals in other fields who want to use analytics as a force multiplier in their organization.
The Data Science Workshop: A New, Interactive Approach to Learning Data Science
by Anthony So Thomas V. Joseph Robert Thas John Andrew Worsley Dr. Samuel AsareCut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner who is getting started for the first time A data science tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book Description You already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead. What you will learn Find out the key differences between supervised and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Learn about different algorithms such as regression, classification, and clustering Discover advanced techniques to improve model ensembling and accuracy Speed up the process of creating new features with automated feature tool Simplify machine learning using open source Python packages Who this book is for Our goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.
The Data Science Workshop: Learn how you can build machine learning models and create your own real-world data science projects, 2nd Edition
by Anthony So Thomas V. Joseph Robert Thas John Andrew Worsley Dr. Samuel AsareGain expert guidance on how to successfully develop machine learning models in Python and build your own unique data platforms Key Features Gain a full understanding of the model production and deployment process Build your first machine learning model in just five minutes and get a hands-on machine learning experience Understand how to deal with common challenges in data science projects Book Description Where there's data, there's insight. With so much data being generated, there is immense scope to extract meaningful information that'll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you'll open new career paths and opportunities. The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You'll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you'll get hands-on with approaches such as grid search and random search. Next, you'll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You'll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch. By the end of this book, you'll have the skills to start working on data science projects confidently. By the end of this book, you'll have the skills to start working on data science projects confidently. What you will learn Explore the key differences between supervised learning and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Understand key concepts such as regression, classification, and clustering Discover advanced techniques to improve the accuracy of your model Understand how to speed up the process of adding new features Simplify your machine learning workflow for production Who this book is for This is one of the most useful data science books for aspiring data analysts, data scientists, database engineers, and business analysts. It is aimed at those who want to kick-start their careers in data science by quickly learning data science techniques without going through all the mathematics behind machine learning algorithms. Basic knowledge of the Python programming language will help you easily grasp the concepts explained in this book.
The Data Visualization Workshop: A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
by Tim Großmann Mario DoblerExplore a modern approach to visualizing data with Python and transform large real-world datasets into expressive visual graphics using this beginner-friendly workshop Key Features Discover the essential tools and methods of data visualization Learn to use standard Python plotting libraries such as Matplotlib and Seaborn Gain insights into the visualization techniques of big companies Book Description Do you want to transform data into captivating images? Do you want to make it easy for your audience to process and understand the patterns, trends, and relationships hidden within your data? The Data Visualization Workshop will guide you through the world of data visualization and help you to unlock simple secrets for transforming data into meaningful visuals with the help of exciting exercises and activities. Starting with an introduction to data visualization, this book shows you how to first prepare raw data for visualization using NumPy and pandas operations. As you progress, you'll use plotting techniques, such as comparison and distribution, to identify relationships and similarities between datasets. You'll then work through practical exercises to simplify the process of creating visualizations using Python plotting libraries such as Matplotlib and Seaborn. If you've ever wondered how popular companies like Uber and Airbnb use geoplotlib for geographical visualizations, this book has got you covered, helping you analyze and understand the process effectively. Finally, you'll use the Bokeh library to create dynamic visualizations that can be integrated into any web page. By the end of this workshop, you'll have learned how to present engaging mission-critical insights by creating impactful visualizations with real-world data. What you will learn Understand the importance of data visualization in data science Implement NumPy and pandas operations on real-life datasets Create captivating data visualizations using plotting libraries Use advanced techniques to plot geospatial data on a map Integrate interactive visualizations to a webpage Visualize stock prices with Bokeh and analyze Airbnb data with Matplotlib Who this book is for The Data Visualization Workshop is for beginners who want to learn data visualization, as well as developers and data scientists who are looking to enrich their practical data science skills. Prior knowledge of data analytics, data science, and visualization is not mandatory. Knowledge of Python basics and high-school-level math will help you grasp the concepts covered in this data visualization book more quickly and effectively.
The Data Visualization Workshop: An Interactive Approach to Learning Data Visualization, 2nd Edition
by Tim Großmann Mario DoblerCut through the noise and get real results with a step-by-step approach to learning data visualization with Python Key Features Ideal for Python beginners getting started with data visualization for the first time A step-by-step data visualization tutorial with exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book Description You already know you want to learn data visualization with Python, and a smarter way to learn is to learn by doing. The Data Visualization Workshop focuses on building up your practical skills so that you can develop clear, expressive real-world charts and diagrams. You'll learn from real examples that lead to real results. Throughout The Data Visualization Workshop, you'll take an engaging step-by-step approach to understand data visualization with Python. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend learning how companies like Uber are using advanced visualization techniques to represent their data visually. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Visualization Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your book. Fast-paced and direct, The Data Visualization Workshop is the ideal companion for Python beginners who want to get up and running with data visualization. You'll visualize your work like a skilled data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead. What you will learn Get to grips with fundamental concepts and conventions of data visualization Learn how to use libraries like NumPy and Pandas to index, slice, and iterate data frames Implement different plotting techniques to produce compelling data visualizations Learn how you can skyrocket your Python data wrangling skills Draw statistical graphics using the Seaborn and Matplotlib libraries Create interactive visualizations and integrate them into any web page Who this book is for Our goal at Packt is to help you be successful, in whatever it is that you choose to do. The Data Visualization Workshop is an ideal tutorial for those who want to perform data visualization with Python and are just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.
The Data Warehouse Lifecycle Toolkit
by Joy Mundy Bob Becker Margy Ross Ralph Kimball Warren ThornthwaiteA thorough update to the industry standard for designing, developing, and deploying data warehouse and business intelligence systemsThe world of data warehousing has changed remarkably since the first edition of The Data Warehouse Lifecycle Toolkit was published in 1998. In that time, the data warehouse industry has reached full maturity and acceptance, hardware and software have made staggering advances, and the techniques promoted in the premiere edition of this book have been adopted by nearly all data warehouse vendors and practitioners. In addition, the term "business intelligence" emerged to reflect the mission of the data warehouse: wrangling the data out of source systems, cleaning it, and delivering it to add value to the business.Ralph Kimball and his colleagues have refined the original set of Lifecycle methods and techniques based on their consulting and training experience. The authors understand first-hand that a data warehousing/business intelligence (DW/BI) system needs to change as fast as its surrounding organization evolves. To that end, they walk you through the detailed steps of designing, developing, and deploying a DW/BI system. You'll learn to create adaptable systems that deliver data and analyses to business users so they can make better business decisions.
The Data Warehouse Toolkit
by Margy Ross Ralph KimballThe latest edition of the single most authoritative guide on dimensional modeling for data warehousing! Dimensional modeling has become the most widely accepted approach for data warehouse design. Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: * Retail sales and e-commerce * Inventory management * Procurement * Order management * Customer relationship management (CRM) * Human resources management * Accounting * Financial services * Telecommunications and utilities * Education * Transportation * Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts. This book is also available as part of the Kimball's Data Warehouse Toolkit Classics Box Set (ISBN: 9780470479575) with the following 3 books: The Data Warehouse Toolkit, 2nd Edition (9780471200246) The Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775) The Data Warehouse ETL Toolkit (9780764567575)
The Data WarehouseETL Toolkit
by Ralph Kimball Joe CasertaCowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copiesDelivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) processDelineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouseOffers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality
The Data Wrangling Workshop: Create your own actionable insights using data from multiple raw sources, 2nd Edition
by Shubhadeep Roychowdhury Brian Lipp Dr. Tirthajyoti SarkarA beginner's guide to simplifying Extract, Transform, Load (ETL) processes with the help of hands-on tips, tricks, and best practices, in a fun and interactive way Key Features Explore data wrangling with the help of real-world examples and business use cases Study various ways to extract the most value from your data in minimal time Boost your knowledge with bonus topics, such as random data generation and data integrity checks Book Description While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined. If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques. This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool. By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources. What you will learn Get to grips with the fundamentals of data wrangling Understand how to model data with random data generation and data integrity checks Discover how to examine data with descriptive statistics and plotting techniques Explore how to search and retrieve information with regular expressions Delve into commonly-used Python data science libraries Become well-versed with how to handle and compensate for missing data Who this book is for The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
The Data-Driven Blockchain Ecosystem: Fundamentals, Applications, and Emerging Technologies
by Seema Sharma Alex Khang Subrata ChowdhuryThis book focuses on futuristic approaches and designs for real-time systems and applications, as well as the fundamental concepts of including advanced techniques and tools in models of data-driven blockchain ecosystems. The Data-Driven Blockchain Ecosystem: Fundamentals, Applications, and Emerging Technologies discusses how to implement and manage processes for releasing and delivering blockchain applications. It presents the core of blockchain technology, IoT-based and AI-based blockchain systems, and various manufacturing areas related to Industry 4.0. The book illustrates how to apply design principles to develop and manage blockchain networks, and also covers the role that cloud computing plays in blockchain applications. All major technologies involved in blockchain-embedded applications are included in this book, which makes it useful to engineering students, researchers, academicians, and professionals interested in the core of blockchain technology.
The Data-driven Organization: Using Data for the Success of Your Company (Business Guides on the Go)
by Jonas RashediData has become an indispensable success factor for every company. However, the road towards a data-driven organization is paved with numerous challenges. This book presents a process model for the path to a data-driven company and provides recommendations for the design of all relevant fields of action: Which structures need to be created? Which systems and processes have proven beneficial? How can the quality of the data be ensured and what requirements exist for a data-driven organization in the areas of governance and communication? And last but not least: How can employees be brought along on the journey and what implications does the data-driven organization have for our corporate culture? The book presents an orientation and action framework for the strategic and operational design of a data-driven organization and is valuable for managers who are involved in data management in companies and organizations.
The DataOps Revolution: Delivering the Data-Driven Enterprise
by Simon TrewinDataOps is a new way of delivering data and analytics that is proven to get results. It enables IT and users to collaborate in the delivery of solutions that help organisations to embrace a data-driven culture. The DataOps Revolution: Delivering the Data-Driven Enterprise is a narrative about real world issues involved in using DataOps to make data-driven decisions in modern organisations. The book is built around real delivery examples based on the author’s own experience and lays out principles and a methodology for business success using DataOps. Presenting practical design patterns and DataOps approaches, the book shows how DataOps projects are run and presents the benefits of using DataOps to implement data solutions. Best practices are introduced in this book through the telling of a story, which relates how a lead manager must find a way through complexity to turn an organisation around. This narrative vividly illustrates DataOps in action, enabling readers to incorporate best practices into everyday projects. The book tells the story of an embattled CIO who turns to a new and untested project manager charged with a wide remit to roll out DataOps techniques to an entire organisation. It illustrates a different approach to addressing the challenges in bridging the gap between IT and the business. The approach presented in this story lines up to the six IMPACT pillars of the DataOps model that Kinaesis (www.kinaesis.com) has been using through its consultants to deliver successful projects and turn around failing deliveries. The pillars help to organise thinking and structure an approach to project delivery. The pillars are broken down and translated into steps that can be applied to real-world projects that can deliver satisfaction and fulfillment to customers and project team members.
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines (Second Edition) (Synthesis Lectures on Computer Architecture #Lecture #24)
by Luiz Andre Barroso Jimmy Clidaras Urs HolzleAs computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. <p>These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. <p><p>Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. <p>The first major update to this lecture is presented after nearly four years of substantial academic and industrial developments in warehouse-scale computing.
The Datapreneurs: The Promise of AI and the Creators Building Our Future
by Steve Hamm Bob MugliaA leader in the data economy explains how we arrived at AI—and how we can navigate its future In The Datapreneurs, Bob Muglia helps us understand how innovation in data and information technology have led us to AI—and how this technology must shape our future. The long-time Microsoft executive, former CEO of Snowflake, and current tech investor maps the evolution of the modern data stack and how it has helped build today&’s economy and society. And he explains how humanity must create a new social contract for the artificial general intelligence (AGI)—autonomous machines intelligent as people—that he expects to arrive in less than a decade. Muglia details his personal experience in the foundational years of computing and data analytics, including with Bill Gates and Sam Altman, the CEO of OpenAI, the creator of ChatGPT, and others that are not household names—yet. He builds upon Isaac Asimov&’s Laws of Robotics to explore the moral, ethical, and legal implications of today&’s smart machines, and how a combination of human and machine intelligence could create an era of progress and prosperity where all the people on Earth can have what they need and want without destroying our natural environment.The Datapreneurs is a call to action. AGI is surely coming. Muglia believes that tech business leaders, ethicists, policy leaders, and even the general public must collaborate answer the short- and long-term questions raised by its emergence. And he argues that we had better get going, because advances are coming so fast that society risks getting caught flatfooted—with potentially disastrous consequences.
The Dawn of Time: An Unofficial Graphic Novel for Minecrafters (The Magic Portal #1)
by Cara J. StevensThe first book in an all-new graphic novel series for Minecrafters—The Magic Portal! In a world where combat games are the key to survival, two rivals get accidentally sucked into a portal that brings them back in time to the very beginning of The End. There, they uncover the ancient secrets of an Enderman&’s unusual behavior. In order to get back home and share this valuable knowledge, Keri and Omar must guide the Endermen to carry out their plan to build the End Portal. The problem is, the Endermen aren&’t so keen on following the plans Keri and Omar have laid out for them. In fact, if they&’re not careful, they&’ll find out just how hostile an Enderman can get. Will Keri learn to trust Omar? Can these two enemies find a way to get along long enough to hatch a plan, convince the Endermen to build the End Portal, and return home without making any waves in their future timeline?
The Death of Truth: How Social Media and the Internet Gave Snake Oil Salesmen and Demagogues the Weapons They Needed to Destroy Trust and Polarize the World--And What We Can Do
by Steven BrillHow did we become a world where facts—shared truths—have lost their power to hold us together as a community, as a country, globally? How have we allowed the proliferation of alternative facts, hoaxes, even conspiracy theories, to destroy our trust in institutions, leaders, and legitimate experts? Best-selling journalist Steven Brill documents the forces and people, from Silicon Valley to Madison Avenue to Moscow to Washington, that have created and exploited this world of chaos and division—and offers practical solutions for what we can do about it."A precise description of the punishment cell we have built around our minds and the first few steps back towards light and air." –Timothy Snyder, Author of On Tyranny and Professor of History, Yale University&“A seminal, ground-breaking, documented and honest examination of two of the central dilemmas of our time—what is truth and where to find it.&” —Bob Woodward, associate editor at The Washington PostAs the cofounder of NewsGuard, a company that tracks online misinformation, Steven Brill has observed the rise of fake news from a front-row seat. In The Death of Truth, with startling, often terrifying clarity, he explains how we got here—and how we can get back to a world where truth matters.None of this—conspiracy theories embraced, expertise ridiculed, empirical evidence ignored—has happened by accident. Brill takes us inside the decisions made by executives in Silicon Valley to code the algorithms embedded in their social media platforms to maximize profits by pushing divisive content. He unravels the ingenious creation of automated advertising buying systems that reward that click-baiting content and penalize reliable news publishers, and describes how the use of these ad-financed, misinformation platforms by politicians, hucksters, and conspiracy theorists deceives ordinary citizens. He documents how the most powerful adversaries of America have used American-made social media and advertising tools against us with massive disinformation campaigns—and how, with the development of generative artificial intelligence, everything could get exponentially worse unless we act. The stakes are high for all of us, including Brill himself, whose company's role in exposing Russian disinformation operations resulted in a Russian agent targeting him and his family.Crucially, Brill lays out a series of provocative but realistic prescriptions for what we can do now to reverse course—proposals certain to stir debate and even action that could curb the power of big tech to profit from division and chaos, tamp down polarization, and restore the trust necessary to bring us together.
The Death of Web 2.0: Ethics, Connectivity and Recognition in the Twenty-First Century
by Greg SinghWith all our contemporary connectivity, are we really connected? What does the nature of connectivity tell us about interpersonal and community relationships? What ethical concerns are raised through an always-on culture? Communication in today’s world is characterised by a condition of persistent, semi-permanent connectivity, which seems to bring us closer together, but which can also be profoundly alienating. The Death of Web 2.0 takes a retrospective look at a moment in recent media history that has had, and will continue to have, a lasting impact upon the predominant attitude towards cultures of connectivity. Greg Singh draws from a range of approaches, intellectual traditions and scholarly disciplines to engage key questions underpinning the contemporary communications media ecosystem. Bringing together influences from communitarian ethics, recognition theory and relational and depth psychology, Singh synthesises key approaches to produce a critical inquiry that projects the tensions at the heart of connectivity as a principle of Web 2.0. He argues that Web 2.0 is a cultural moment that is truly over, and that what is popularly described as 'Web 2.0' is an altogether different set of principles and practices. The Death of Web 2.0 recognises the consequences of our 'always-on' culture, where judgments are made quickly and where impacts can be far-reaching, affecting our relationships, wellbeing, mental health and the health of our communities, and it concludes by asking what an ethics of connectivity would look like. This unique interdisciplinary work will be essential reading for academics and students of Jungian and post-Jungian studies, media and cultural studies and psychosocial studies as well as anyone interested in the social implications of new media.
The Death of the Internet
by Markus JakobssonFraud poses a significant threat to the Internet. 1.5% of all online advertisements attempt to spread malware. This lowers the willingness to view or handle advertisements, which will severely affect the structure of the web and its viability. It may also destabilize online commerce. In addition, the Internet is increasingly becoming a weapon for political targets by malicious organizations and governments. This book will examine these and related topics, such as smart phone based web security. This book describes the basic threats to the Internet (loss of trust, loss of advertising revenue, loss of security) and how they are related. It also discusses the primary countermeasures and how to implement them.
The Debates Shaping Spectrum Policy
by Martin SimsWhat debates have caused spectrum policy to change course and which will determine its future direction? This book examines these issues through a series of chapters from a range of notable experts. The backdrop is a period of turbulent change in what was once a quiet backwater. The past quarter century has seen wireless connectivity go from nice-to-have luxury to the cornerstone of success as nations battle for leadership of the digital economy. The change has been reflected in the crucial role now played by market's mechanisms in a field once dominated by administrative decisions. Spectrum policy’s goals have moved far beyond the efficient use of the airwaves to include encouraging economic development, investment, innovation, sustainability and digital inclusivity. Are historic procedures still appropriate in the face of this multiplicity of demands? Are market mechanisms like auctions still the best way to deliver what has become essential infrastructure? Does the process of international coordination need to change? Is spectrum policy’s effectiveness limited by the power of global economic forces? Can it reduce rather than add to global warming? Where does 6G and AI fit in? Is public perception the new spectrum policy battle ground? These are all issues examined in The Debates Shaping Spectrum Policy.
The Debugger's Handbook
by J.F. DiMarzioFor today's programmers, it is impossible to foresee every input, every usage scenario, and every combination of applications that can cause errors when run simultaneously. Given all of these unknowns, writing absolutely bug-free code is unachievable. But it is possible, with the right knowledge, to produce nearly bug-free code and The Debugger's H
The Decentring of the Traditional University: The Future of (Self) Education in Virtually Figured Worlds
by Russell FrancisThe Decentring of the Traditional University provides a unique perspective on the implications of media change for learning and literacy that allows us to peer into the future of (self) education. Each chapter draws on socio-cultural and activity theory to investigate how resourceful students are breaking away from traditional modes of instruction and educating themselves through engagement with a globally interconnected web-based participatory culture. The argument is developed with reference to the findings of an ethnographic study that focused on university students’ informal uses of social and participatory media. Each chapter draws attention to the shifting locus of agency for regulating and managing learning and describes an emergent genre of learning activity. For example, Francis explores how students are cultivating and nurturing globally distributed funds of living knowledge that transcend institutional boundaries and describes students learning through serious play in virtually figured worlds that support radically personalised lifelong learning agendas. These stories also highlight the challenges and choices learners confront as they struggle to negotiate the faultlines of media convergence and master the new media literacies required to exploit the full potential of Web 2.0 as a learning resource. Overall, this compelling argument proposes that we are witnessing a period of historic systemic change in the culture of university learning as an emergent web-based participatory culture starts to disrupt and displace a top-down culture industry model of education that has evolved around the medium of the book. As a result, Francis argues that we need to re-conceive higher education as an identity-project in which students work on their projective identities (or imagined future selves) through engagement with both formal and informal learning activities.