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Data and Applications Security and Privacy XXXVII: 37th Annual IFIP WG 11.3 Conference, DBSec 2023, Sophia-Antipolis, France, July 19–21, 2023, Proceedings (Lecture Notes in Computer Science #13942)

by Vijayalakshmi Atluri Anna Lisa Ferrara

This volume LNCS 13942 constitutes the refereed proceedings of the 37th Annual IFIP WG 11.3 Conference, DBSec 2023, in Sophia-Antipolis, France, July 19–21, 2023. The 19 full papers presented together with 5 short papers were carefully reviewed and selected from 56 submissions. The conference focuses on secure data sharing; access control and vulnerability assessment; machine learning; and mobile applications.

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World

by Bruce Schneier

You are under surveillance right now.<P><P> Your cell phone provider tracks your location and knows who’s with you. Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you’re thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it.<P> The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we’re offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches.<P> Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we’ve gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He shows us exactly what we can do to reform our government surveillance programs and shake up surveillance-based business models, while also providing tips for you to protect your privacy every day. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again.

Data and Society: A Critical Introduction

by Anne Beaulieu Sabina Leonelli

Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.

Data and Society: A Critical Introduction

by Anne Beaulieu Sabina Leonelli

Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.

Data and the City (Regions and Cities)

by Rob Kitchin Tracey P. Lauriault Gavin McArdle

There is a long history of governments, businesses, science and citizens producing and utilizing data in order to monitor, regulate, profit from and make sense of the urban world. Recently, we have entered the age of big data, and now many aspects of everyday urban life are being captured as data and city management is mediated through data-driven technologies. Data and the City is the first edited collection to provide an interdisciplinary analysis of how this new era of urban big data is reshaping how we come to know and govern cities, and the implications of such a transformation. This book looks at the creation of real-time cities and data-driven urbanism and considers the relationships at play. By taking a philosophical, political, practical and technical approach to urban data, the authors analyse the ways in which data is produced and framed within socio-technical systems. They then examine the constellation of existing and emerging urban data technologies. The volume concludes by considering the social and political ramifications of data-driven urbanism, questioning whom it serves and for what ends. This book, the companion volume to 2016’s Code and the City, offers the first critical reflection on the relationship between data, data practices and the city, and how we come to know and understand cities through data. It will be crucial reading for those who wish to understand and conceptualize urban big data, data-driven urbanism and the development of smart cities.

Data Augmentation, Labelling, and Imperfections: Second MICCAI Workshop, DALI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings (Lecture Notes in Computer Science #13567)

by Hien V. Nguyen Sharon X. Huang Yuan Xue

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022.DALI 2022 accepted 12 papers from the 22 submissions that were reviewed. The papers focus on rigorous study of medical data related to machine learning systems.

Data Baby: My Life in a Psychological Experiment

by Susannah Breslin

A Belletrist Book Pick​ for December 2023Lab Girl meets Brain on Fire in this provocative and poignant memoir delving into a woman's formative experiences as a veritable "lab rat" in a lifelong psychological study, and her pursuit to reclaim autonomy and her identity as a adult. What if your parents turn you into a human lab rat when you&’re a child? Will that change the story of your life? Will that change who you are? When Susannah Breslin is a toddler, her parents enroll her in an exclusive laboratory preschool at the University of California, Berkeley, where she becomes one of over a hundred children who are research subjects in an unprecedented thirty-year study of personality development that predicts who she and her cohort will grow up to be. Decades later, trapped in what she feels is an abusive marriage and battling breast cancer, she starts to wonder how growing up under a microscope shaped her identity and life choices. Already a successful journalist, she makes her own curious history the subject of her next investigation. From experiment rooms with one-way mirrors, to children&’s puzzles with no solutions, to condemned basement laboratories, her life-changing journey uncovers the long-buried secrets hidden behind the renowned study. The question at the gnarled heart of her quest: Did the study know her better than she knew herself? At once bravely honest and sharply witty, Data Baby is a compelling and provocative account of a woman&’s quest to find her true self, and an unblinking exploration of why we turn out as we do. Few people in all of history have been studied from such a young age and for as long as this author, but the message of her book is universal. In an era when so many of us are looking to technology to tell us who to be, it&’s up to us to discover who we actually are.

Data-Based Child Advocacy: Using Statistical Indicators to Improve the Lives of Children (SpringerBriefs in Well-Being and Quality of Life Research #0)

by William P. O'Hare

This book locates, organizes and summarizes information about the use of child indicators in an advocacy context. It provides a conceptual framework that allows readers to see a wide variety of work as part of a unified field. It provides a description of key concepts and illustrates these concepts by offering many examples from a range of countries and a wide variety of applications. It covers work from governments, non-governmental organization and academics. It describes such aspects as the use of data to educate and increase public awareness, as well as to monitor, set goals and evaluate programs serving children. A growing number of organizations and people are focusing on measuring and monitoring the well-being of children and these child well-being data are often employed in ways that go beyond what is typically considered scholarship. Many of these applications involve some type of advocacy activity. Yet, there is very little in the literature about the use of child indicators in an advocacy context. This book provides a framework for scholars in a variety of disciplines that will help them to structure their thinking about the use of such indicators in a public context.

Data-Centric Biology: A Philosophical Study

by Sabina Leonelli

In recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.

Data-centric Living: Algorithms, Digitization and Regulation

by Sridhar V.

This book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.

Data Collection in Fragile States: Innovations from Africa and Beyond

by Johannes Hoogeveen Utz Pape

‘This open access book addresses an urgent issue on which little organized information exists. It reflects experience in Africa but is highly relevant to other fragile states as well.’ —Constantine Michalopoulos, John Hopkins University, USA and former Director of Economic Policy and Co-ordination at the World BankFragile countries face a triple data challenge. Up-to-date information is needed to deal with rapidly changing circumstances and to design adequate responses. Yet, fragile countries are among the most data deprived, while collecting new information in such circumstances is very challenging. This open access book presents innovations in data collection developed with decision makers in fragile countries in mind. Looking at innovations in Africa from mobile phone surveys monitoring the Ebola crisis, to tracking displaced people in Mali, this collection highlights the challenges in data collection researchers face and how they can be overcome.

Data Collection in Sociolinguistics: Methods and Applications

by Christine Mallinson Becky Childs Gerard Van Herk

This edited volume provides up-to-date, succinct, relevant, and informative discussion about methods of data collection in sociolinguistic research. It covers the main areas of research design, conducting research, and sharing data findings with longer chapters and shorter vignettes written by a range of top sociolinguists, both veteran and emerging scholars. Here is the one-stop, go-to guide for the numerous quantitative, qualitative, and mixed methods that are used in sociolinguistic research, ensuring that Data Collection in Sociolinguistics will be not only useful in the classroom but also as a reference tool for active researchers. For more information, visit sociolinguisticdatacollection.com.

Data Conscience: Algorithmic Siege on our Humanity

by Brandeis Hill Marshall

DATA CONSCIENCE ALGORITHMIC S1EGE ON OUR HUM4N1TY EXPLORE HOW D4TA STRUCTURES C4N HELP OR H1NDER SOC1AL EQU1TY Data has enjoyed ‘bystander’ status as we’ve attempted to digitize responsibility and morality in tech. In fact, data’s importance should earn it a spot at the center of our thinking and strategy around building a better, more ethical world. It’s use—and misuse—lies at the heart of many of the racist, gendered, classist, and otherwise oppressive practices of modern tech. In Data Conscience: Algorithmic Siege on our Humanity, computer science and data inclusivity thought leader Dr. Brandeis Hill Marshall delivers a call to action for rebel tech leaders, who acknowledge and are prepared to address the current limitations of software development. In the book, Dr. Brandeis Hill Marshall discusses how the philosophy of “move fast and break things” is, itself, broken, and requires change. You’ll learn about the ways that discrimination rears its ugly head in the digital data space and how to address them with several known algorithms, including social network analysis, and linear regression A can’t-miss resource for junior-level to senior-level software developers who have gotten their hands dirty with at least a handful of significant software development projects, Data Conscience also provides readers with: Discussions of the importance of transparency Explorations of computational thinking in practice Strategies for encouraging accountability in tech Ways to avoid double-edged data visualization Schemes for governing data structures with law and algorithms

Data Culture: Develop An Effective Data-Driven Organization

by Dr Shorful Islam

Organizations often start their data journey by either procuring the technology or hiring the people. However, without an effective data-driven culture in place, they can struggle to derive value from their investments.Data Culture explores how data leaders can develop and nurture a data-driven culture tailored to their organization's needs. It outlines the types of data leadership and teams needed and the key building blocks for success, such as team recruitment, building and training, leadership, process, behavioural change management, developing, sustaining and measuring a data culture, company values and everyday decision making. It also explores the nuances of how different types of data cultures work with different types of companies, what to avoid and the differences between building a data culture from scratch and changing an existing data culture from within.With this hands-on guide, senior data leader Shorful Islam takes readers through how to successfully establish or change a data culture, sharing his expertise in behavioural change psychology and two decades of experience in fostering data culture in organizations. Supported throughout by real-world examples and cases, this will be an essential read for all data leaders and anyone involved in developing a data-driven organizational culture.

The Data Detective: Ten Easy Rules to Make Sense of Statistics

by Tim Harford

From &“one of the great (greatest?) contemporary popular writers on economics&” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics.Today we think statistics are the enemy, numbers used to mislead and confuse us. That&’s a mistake, Tim Harford says in The Data Detective. We shouldn&’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often &“the only way of grasping much of what is going on around us.&” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter.As &“perhaps the best popular economics writer in the world&” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.

Data Distribution: Managing the Environment (Routledge Revivals #Vol. 4)

by Richard Williams

Published in 1992. Business information has evolved from typewriter/card index (decentralized) through the era of DP Department and mainframe (centralized) to present mix with PCs and networks (distributed). This book demonstrates how data distribution can function in the best interests of organizations, through a managed environment. It looks at what is needed from the systems professionals to support current methods; reporting actual experience, defining techniques, and examining the opportunities and challenges.

Data Driven: Truckers, Technology, and the New Workplace Surveillance

by Karen Levy

A behind-the-scenes look at how digital surveillance is affecting the trucking way of lifeLong-haul truckers are the backbone of the American economy, transporting goods under grueling conditions and immense economic pressure. Truckers have long valued the day-to-day independence of their work, sharing a strong occupational identity rooted in a tradition of autonomy. Yet these workers increasingly find themselves under many watchful eyes. Data Driven examines how digital surveillance is upending life and work on the open road, and raises crucial questions about the role of data collection in broader systems of social control.Karen Levy takes readers inside a world few ever see, painting a bracing portrait of one of the last great American frontiers. Federal regulations now require truckers to buy and install digital monitors that capture data about their locations and behaviors. Intended to address the pervasive problem of trucker fatigue by regulating the number of hours driven each day, these devices support additional surveillance by trucking firms and other companies. Traveling from industry trade shows to law offices and truck-stop bars, Levy reveals how these invasive technologies are reconfiguring industry relationships and providing new tools for managerial and legal control—and how truckers are challenging and resisting them.Data Driven contributes to an emerging conversation about how technology affects our work, institutions, and personal lives, and helps to guide our thinking about how to protect public interests and safeguard human dignity in the digital age.

Data-Driven HR: How to Use Analytics and Metrics to Drive Performance

by Bernard Marr

Traditionally seen as a purely people function unconcerned with numbers, HR is now uniquely placed to use company data to drive performance, both of the people in the organization and the organization as a whole. Data-Driven HR is a practical guide which enables HR professionals to leverage the value of the vast amount of data available at their fingertips. Covering how to identify the most useful sources of data, collect information in a transparent way that is in line with data protection requirements and turn this data into tangible insights, this book marks a turning point for the HR profession. Covering all the key elements of HR including recruitment, employee engagement, performance management, wellbeing and training, Data-Driven HR examines the ways data can contribute to organizational success by, among other things, optimizing processes, driving performance and improving HR decision making. Packed with case studies and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.

Data-Driven HR: How to Use AI, Analytics and Data to Drive Performance

by Bernard Marr

How can HR professionals utilize and leverage their organization's data effectively, with the use of AI, for more talent attraction, better employee engagement and higher talent retention to ultimately drive performance?AI is now an integral part of being data-driven. With this updated edition of Data-Driven HR, practitioners can unlock business potential and success through data and analytics. Covering topics such as recruitment, employee engagement, performance management, wellbeing and training, HR practitioners can benefit from knowing how to really be data-driven through the use of data and AI. HR teams will learn how to identify business goals, scrutinize useful sources of data and gain rich and diverse insights from their vast amounts of data. This book brings guidance on how to manage challenges that come with data and AI, as well as how to responsibly and transparently use data to improve decision making. It also includes predictive analytics and how to place warning systems into databases for any potential workforce issues. Packed with practical advice, key takeaways and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.

Data-driven Modelling of Structured Populations: A Practical Guide to the Integral Projection Model (Lecture Notes on Mathematical Modelling in the Life Sciences)

by Mark Rees Stephen P. Ellner Dylan Z. Childs

This book is a "How To" guide formodeling population dynamics using Integral Projection Models (IPM) startingfrom observational data. It is written by a leading research team in this areaand includes code in the R language (in the text and online) to carry out allcomputations. The intended audience are ecologists, evolutionary biologists,and mathematical biologists interested in developing data-driven models foranimal and plant populations. IPMs may seem hard as they involve integrals. Theaim of this book is to demystify IPMs, so they become the model of choice forpopulations structured by size or other continuously varying traits. The bookuses real examples of increasing complexity to show how the life-cycle of thestudy organism naturally leads to the appropriate statistical analysis, whichleads directly to the IPM itself. A wide range of model types and analyses arepresented, including model construction, computational methods, and theunderlying theory, with the more technical material in Boxes and Appendices. Self-contained R code which replicates all of the figures and calculationswithin the text is available to readers on GitHub. Stephen P. Ellner is Horace White Professor of Ecology and Evolutionary Biology at Cornell University, USA; Dylan Z. Childs is Lecturer and NERC Postdoctoral Fellow in the Department of Animal and Plant Sciences at The University of Sheffield, UK; Mark Rees is Professor in the Department of Animal and Plant Sciences at The University of Sheffield, UK.

Data-driven Organization Design

by Rupert Morrison

Data is changing the nature of competition. Making sense of it is tough. Taking advantage of it is tougher. There is a business opportunity for organizations to use data and analytics to transform business performance. Organizations are by their nature complex. They are a constantly evolving system made up of objectives, processes designed to meet those objectives, people with skills and behaviours to do the work required, and all of this organised in a governance structure. It is dynamic, fluid and constantly moving over time. Using data and analytics you can connect all the elements of the system to design an environment for people to perform; an organization which has the right people, in the right place, doing the right things, at the right time. Only when everyone performs to their potential, do organizations have a hope of getting and sustaining a competitive edge. Data-driven Organization Design provides a practical framework for HR and Organization design practitioners to build a baseline of data, set objectives, carry out fixed and dynamic process design, map competencies, and right-size the organization. It shows how to collect the right data, present it meaningfully and ask the right questions of it. Whether looking to implement a long term transformation, large redesign, or a one-off small scale project, this book will show you how to make the most of your organizational data and analytics to drive business performance.

Data-Driven Organization Design: Delivering Perpetual Performance Gains Through the Organizational System

by Rupert Morrison

Understand how to drive business performance with your organizational data and analytics in the second edition of Data-Driven Organization Design.Using data and analytics is a key opportunity for businesses to transform performance and achieve success. With a data-driven approach, all the elements of the organizational system can be connected to design an environment in which people can excel and attain competitive advantage. Data-Driven Organization Design provides a practical framework for HR and organization design practitioners to build a baseline of data, set objectives, carry out fixed and dynamic process design, map competencies, and right-size the organization. It shows how to collect the right data, present it meaningfully and ask the most relevant questions of it to help complex, fluid organizations constantly evolve and meet moving objectives. This updated second edition contains new material on organizational planning and analysis, role design and job architecture, position management lifecycle and delta reporting. Alongside this, new case studies and examples will show how these approaches have been applied in practice. Whether planning a long-term transformation, a large redesign or an individual small project, Data-Driven Organization Design will demonstrate how to make the most of your organizational data and analytics to drive business performance.

Data-Driven Personalization: How to Use Consumer Insights to Generate Customer Loyalty

by Zontee Hou

Make your marketing truly resonate by personalizing every message, powered by data, research and behavioral economics. To break through the noise, marketers today need to be hyper-relevant to their customers. To do that takes data and a deep understanding of your audience. Data-Driven Personalization breaks down the best ways to reach new customers and better engage your best customers. By combining principles of persuasion, behavioral economics and industry research, this book provides readers with an actionable blueprint for how to implement a customer-centric approach to marketing that will drive results. The book is broken into six parts that detail everything from what data is most valuable for personalization to how to build a data-driven marketing team that's prepared for the next five years and beyond. Each chapter includes actionable insights to guide marketers as they implement a data-driven personalization approach to their strategy. The chapters also focus on hands-on tactics like identifying messages that will move the needle with customers, how to generate seamless omnichannel experiences and how to balance personalization with data privacy. The book features case studies from top brands, including FreshDirect, Target, Adobe, Cisco and Spotify.

Data-Driven Policy Impact Evaluation: How Access to Microdata is Transforming Policy Design

by Nuno Crato Paolo Paruolo

In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.

The Data-Driven Project Manager: A Statistical Battle Against Project Obstacles

by Mario Vanhoucke

Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools.The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles.Data-driven project management is known in the academic literature as “dynamic scheduling” or “integrated project management and control.” It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows:Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project’s time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project’s time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project’s performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used.What You'll LearnImplement a data-driven project management methodology (also known as "dynamic scheduling") which allows project managers to plan, monitor, and control projects while delivering them on time and within budgetStudy different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM)Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project controlWho This Book Is ForProject managers looking to learn data-driven project management (or "dynamic scheduling") via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles

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