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Data Analytics Initiatives: Managing Analytics for Success
by Ondřej Bothe Ondřej Kubera David Bednář Martin Potančok Ota NovotnýThe categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.
Data Analytics Made Easy: Use machine learning and data storytelling in your work without writing any code
by Andrea De Mauro Francesco Marzoni Andrew J. WalterMake informed decisions using data analytics, machine learning, and data visualizationsKey FeaturesTake raw data and transform it to add value to your organizationLearn the art of telling stories with your data to engage with your audienceApply machine learning algorithms to your data with a few clicks of a buttonBook DescriptionData analytics has become a necessity in modern business, and skills such as data visualization, machine learning, and digital storytelling are now essential in every field. If you want to make sense of your data and add value with informed decisions, this is the book for you. Data Analytics Made Easy is an accessible guide to help you start analyzing data and quickly apply these skills to your work. It focuses on how to generate insights from your data at the click of a few buttons, using the popular tools KNIME and Microsoft Power BI. The book introduces the concepts of data analytics and shows you how to get your data ready and apply machine learning algorithms. Implement a complete predictive analytics solution with KNIME and assess its level of accuracy. Create impressive visualizations with Microsoft Power BI and learn the greatest secret in successful analytics – how to tell a story with your data. You'll connect the dots on the various stages of the data-to-insights process and gain an overview of alternative tools, including Tableau and H20 Driverless AI. By the end of this book, you will have learned how to implement machine learning algorithms and sell the results to your customers without writing a line of code.What you will learnUnderstand the potential of data and its impact on any businessInfluence business decisions with effective data storytelling when delivering insightsUse KNIME to import, clean, transform, combine data feeds, and automate recurring workflowsLearn the basics of machine learning and AutoML to add value to your organizationBuild, test, and validate simple supervised and unsupervised machine learning models with KNIMEUse Power BI and Tableau to build professional-looking and business-centric visuals and dashboardsWho this book is forWhether you are working with data experts or want to find insights in your business' data, you'll find this book an effective way to add analytics to your skill stack.No previous math, statistics, or computer science knowledge is required.
Data Analytics & Visualization All-in-One For Dummies
by Jack A. Hyman Luca Massaron Paul McFedries John Paul Mueller Lillian Pierson Jonathan Reichental Joseph Schmuller Alan R. Simon Allen G. TaylorInstall data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sources Organize and analyze data Use data to tell a story with Tableau Expand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.
Data and Analytics Strategy for Business: Unlock Data Assets and Increase Innovation with a Results-Driven Data Strategy
by Simon Asplen-TaylorFor many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business. Most businesses have a wealth of data buried in their systems which, if used effectively, could increase revenue, reduce costs and risk and improve customer satisfaction and employee experience. Beginning with how to choose projects which reflect your organization's goals and how to make the business case for investing in data, this book then takes the reader through the five 'waves' of organizational data maturity. It takes the reader from getting started on the data journey with some quick wins, to how data can help your business become a leading innovator which systematically outperforms competitors.Data and Analytics Strategy for Business outlines how to build consistent, high-quality sources of data which will create business value and explores how automation, AI and machine learning can improve performance and decision making. Filled with real-world examples and case studies, this book is a stage-by-stage guide to designing and implementing a results-driven data strategy.
Data and Decision Sciences in Action: Proceedings of the Australian Society for Operations Research Conference 2016 (Lecture Notes in Management and Industrial Engineering)
by Richard Davis Hussein A. Abbass Ruhul Sarker Simon Dunstall Philip Kilby Leon YoungOffering a concise and multidisciplinary reference guide to the state of the art in Australian operations research, this book will be of great value to academics working in many disciplines associated with operations research, as well as industrial practitioners engaged in planning, scheduling and logistics. Over 60 papers, with topics ranging from academic research techniques and case studies to industrial and administrative best practices in operations research, address aspects such as: * optimization, combinatorial optimization, decision analysis, supply-chain management, queuing and routing, and project management; and * logistics, government, cyber security, health-care systems, mining and material processing, ergonomics and human factors, space applications, telecommunications and transportation, among many others. This book presents the Proceedings of the National Conference of the Australian Society for Operations Research, the premier professional organization for Australian academics and practitioners working in optimization and other disciplines related to operations research. The conference was held in Canberra in November 2016.
Data and Decision Sciences in Action 2: Proceedings of the ASOR/DORS Conference 2018 (Lecture Notes in Management and Industrial Engineering)
by Andreas T. Ernst Simon Dunstall Rodolfo García-Flores Marthie Grobler David MarlowThis book constitutes the proceedings of the Joint 2018 National Conferences of the Australian Society for Operations Research (ASOR) and the Defence Operations Research Symposium (DORS). Offering a fascinating insight into the state of the art in Australian operations research, this book is of great interest to academics and other professional researchers working in operations research and analytics, as well as practitioners addressing strategic planning, operations management, and other data-driven decision-making challenges in the domains of commerce, industry, defence, the environment, humanitarianism, and agriculture. The book comprises 21 papers on topics ranging from methodological advances to case studies, and addresses application domains including supply chains, government services, defence, cybersecurity, healthcare, mining and material processing, agriculture, natural hazards, telecommunications and transportation.ASOR is the premier professional organization for Australian academics and practitioners working in optimization and other disciplines related to operations research. The conference was held in Melbourne, Australia, in December 2018.
Data and Democracy at Work: Advanced Information Technologies, Labor Law, and the New Working Class
by Brishen RogersAn exploration of how major companies have used advanced information technologies to limit worker power, and how labor law reform could reverse that trend.As our economy has shifted away from industrial production and service industries have become dominant, many of the nation's largest employers are now in fields like retail, food service, logistics, and hospitality. These companies have turned to data-driven surveillance technologies that operate over a vast distance, enabling cheaper oversight of massive numbers of workers. Data and Democracy at Work argues that companies often use new data-driven technologies as a power resource—or even a tool of class domination—and that our labor laws allow them to do so.Employers have established broad rights to use technology to gather data on workers and their performance, to exclude others from accessing that data, and to use that data to refine their managerial strategies. Through these means, companies have suppressed workers' ability to organize and unionize, thereby driving down wages and eroding working conditions.Labor law today encourages employer dominance in many ways—but labor law can also be reformed to become a tool for increased equity. The COVID-19 pandemic and subsequent Great Resignation have indicated an increased political mobilization of the so-called essential workers of the pandemic, many of them service industry workers. This book describes the necessary legal reforms to increase workers' associational power and democratize workplace data, establishing more balanced relationships between workers and employers and ensuring a brighter and more equitable future for us all.
Data and the American Dream: Contemporary Social Controversies and the American Community Survey
by Matthew J. HolianThis book paints a portrait of social life in America by providing an accessible discussion of empirical economics research on issues such as illegal immigration, health care and climate change. All the studies in this book use the same data source: individual responses to the American Community Survey (ACS), the nation's largest household survey.The author identifies studies that clearly illustrate core econometric methods (such as regression control and difference-in-differences), replicates key statistics from the studies, and helps the reader to carefully interpret the statistics. This book has a companion website with replication files in R and Stata format. The Appendix to this book contains a guide to using the free R software, downloading the ACS and other public-use microdata, and running the replication files, which assumes no background knowledge on the part of the reader beyond introductory statistics. By opening up the hood on how top scholars use core econometric methods to analyze large data sets, a motivated reader with a decent computer and Internet connection can use this book to learn not only how to replicate published research, but also to extend the analysis to create new knowledge about important social phenomena. A more casual reader can skip the online supplements and still gain data-driven insights into social and economic behavior. The book concludes by describing how careful empirical estimates can guide decision making, through cost-benefit analysis, to find public policies that lead to greater happiness while accounting for environmental, public health and other impacts.With its accessible discussion, glossary, detailed learning goals, end of chapter review questions and companion resources, this book is ideal for use as a supplementary volume in introductory econometrics or research methods courses.
Data and the City (Regions and Cities)
by Rob Kitchin Tracey P. Lauriault Gavin McArdleThere 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.
The Data Asset: How Smart Companies Govern Their Data for Business Success
by Tony FisherAn indispensable guide that shows companies how to treat data as a strategic asset Organizations set their business strategy and direction based on information that is available to executives. The Data Asset provides guidance for not only building the business case for data quality and data governance, but also for developing methodologies and processes that will enable your organization to better treat its data as a strategic asset. Part of Wiley's SAS Business Series, this book looks at Business Case Building; Maturity Model and Organization Capabilities; 7-Step Programmatic Approach for Success; and Technologies Required for Effective Data Quality and Data Governance and, within these areas, covers Risk mitigation Cost control Revenue optimization Undisciplined and reactive organizations Proactive organizations Analysis, improvement, and control technology Whether you're a business manager or an IT professional, The Data Asset reveals the methodology and technology needed to approach successful data quality and data governance initiatives on an enterprise scale.
Data Breach at Equifax
by Jonah S. Goldberg Quinn Pitcher Suraj SrinivasanExamining the cause of and response to the 2017 data breach at Equifax that exposed the information of over 145 million consumers.
Data Breach at Equifax
by Quinn Pitcher Suraj SrinivasanExamining the cause of and response to the 2017 data breach at Equifax that exposed the information of over 145 million consumers.
Data Breach at Equifax
by Suraj Srinivasan Quinn PitcherExamining the cause of and response to the 2017 data breach at Equifax that exposed the information of over 145 million consumers.
Data Capital: How Data is Reinventing Capital for Globalization
by Chunlei TangThis book defines and develops the concept of data capital. Using an interdisciplinary perspective, this book focuses on the key features of the data economy, systematically presenting the economic aspects of data science. The book (1) introduces an alternative interpretation on economists’ observation of which capital has changed radically since the twentieth century; (2) elaborates on the composition of data capital and it as a factor of production; (3) describes morphological changes in data capital that influence its accumulation and circulation; (4) explains the rise of data capital as an underappreciated cause of phenomena from data sovereign, economic inequality, to stagnating productivity; (5) discusses hopes and challenges for industrial circles, the government and academia when an intangible wealth brought by data (and information or knowledge as well); (6) proposes the development of criteria for measuring regulating data capital in the twenty-first century for regulatory purposes by looking at the prospects for data capital and possible impact on future society. Providing the first a thorough introduction to the theory of data as capital, this book will be useful for those studying economics, data science, and business, as well as those in the financial industry who own, control, or wish to work with data resources.
Data Center Storage: Cost-Effective Strategies, Implementation, and Management
by Hubbert SmithWe overspend on data center storage ... yet, we fall short of business requirements. It's not about the technologies. It's about the proper application of technologies to deliver storage services efficiently and affordably. It's about meeting business requirements dependent on data center storage. Spend less, deliver more. Data Center Storage: Cost-Effective Strategies, Implementation, and Management provides an industry insider's insight on how to properly scope, plan, evaluate, and implement storage technologies to maximize performance, capacity, reliability, and power savings. It provides business and use-case focused coverage of storage technology, including storage area networks (SAN), capacity-optimized drives, and solid-state drives. It offers key insights on financially responsible spending for data center storage. Delivered in accessible language, the book starts with a discussion of the business merits of replacing direct attached, compartmentalized storage with consolidated SAN-attached storage. The author advises on the use of service level applications (SLAs) as a tool to drive business unit collaboration with IT and prioritize those actions that impact productivity and profit from those that are less critical. This business guide to applied technologies disassembles big problems into digestible segments to help you understand, quantify, and fix any problems that arise as you work towards meeting your growing storage needs. The book builds on the consolidation and SLA driven approach to take advantage of the compelling benefits and potential savings of managed hosting and cloud storage.
Data Center Virtualization Certification: Everything you need to achieve 2V0-622 certification – with exam tips and exercises
by Andrea Mauro Paolo ValsecchiDeploy and configure vSphere infrastructure and learn to effectively create and administer vSphere virtual machinesKey FeaturesImplement advanced network virtualization techniquesConfigure and administer vSphere high availabilityEnhance your data center virtualization skills with practice questions and mock testsBook DescriptionThis exam guide enables you to install, configure, and manage the vSphere 6.5 infrastructure in all its components: vCenter Server, ESXi hosts, and virtual machines, while helping you to prepare for the industry standard certification.This data center book will assist you in automating administration tasks and enhancing your environment’s capabilities. You will begin with an introduction to all aspects related to security, networking, and storage in vSphere 6.5. Next, you will learn about resource management and understand how to back up and restore the vSphere 6.5 infrastructure. As you advance, you will also cover troubleshooting, deployment, availability, and virtual machine management. This is followed by two mock tests that will test your knowledge and challenge your understanding of all the topics included in the exam.By the end of this book, you will not only have learned about virtualization and its techniques, but you’ll also be prepared to pass the VCP6.5-DCV (2V0-622) exam.What you will learnDeploy and configure vSphere infrastructureCreate and administer vSphere virtual machinesOptimize, secure, and troubleshoot all vSphere componentsImplement vSphere HA on a vSAN clusterUnderstand how to back up and restore your vSphere 6.5 infrastructureTest your understanding of key concepts required through sample questionsWho this book is forIf you are interested in achieving Data Center Virtualization certification, this is the book is for you. You will also benefit from this book if you are a system administrator or network engineer. Some prior knowledge of virtualization can assist you in understanding key concepts covered in the book.
Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem
by Alex Khang Geeta Rana R. K. Tailor Vugar AbdullayevThe book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem. Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare. This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
Data-Centric Business and Applications: Evolvements in Business Information Processing and Management (Volume 3) (Lecture Notes on Data Engineering and Communications Technologies #42)
by Dmytro Ageyev Tamara Radivilova Natalia KryvinskaBuilding on the authors’ previous work, this book addresses key processes and procedures used in information/data processing and management. Modern methods of business information processing, which draw on artificial intelligence, big data, and cloud-based storage and processing, are opening exciting new opportunities for doing business on the basis of information technologies. Thus, in this third book, the authors continue to explore various aspects – technological as well as business and social – of the information industries. Further, they analyze the challenges and opportunities entailed by these kinds of business.
Data-Centric Business and Applications: ICT Systems—Theory, Radio-Electronics, Information Technologies and Cybersecurity (Lecture Notes on Data Engineering and Communications Technologies #69)
by Dmytro Ageyev Tamara Radivilova Natalia KryvinskaThis book, building on the authors’ previous work, presents new communication and networking technologies, challenges and opportunities of information/data processing and transmission. It also discusses the development of more intelligent and efficient communication technologies, which are an essential part of current day-to-day life. Information and Communication Technologies (ICTs) have an enormous impact on businesses and our day-to-day lives over the past three decades and continue to do so. Modern methods of business information processing are opening exciting new opportunities for doing business on the basis of information technologies. The book contains research that spans a wide range of communication and networking technologies, including wireless sensor networks, optical and telecommunication networks, storage area networks, error-free transmission and signal processing.
Data-Centric Business and Applications: Evolvements in Business Information Processing and Management—Volume 1 (Lecture Notes on Data Engineering and Communications Technologies #20)
by Natalia Kryvinska Michal GregušThis book discusses processes and procedures in information/data processing and management. The global market is becoming more and more complex with an increased availability of data and information, and as a result doing business with information is becoming more popular, with a significant impact on modern society immensely. This means that there is a growing need for a common understanding of how to create, access, use and manage business information. As such this book explores different aspects of data and information processing, including information generation, representation, structuring, organization, storage, retrieval, navigation, human factors in information systems, and the use of information. It also analyzes the challenges and opportunities of doing business with information, and presents various perspectives on business information managing.
Data-Centric Business and Applications: Towards Software Development (Volume 4) (Lecture Notes on Data Engineering and Communications Technologies #40)
by Aneta Poniszewska-Marańda Natalia Kryvinska Stanisław Jarząbek Lech MadeyskiThis book explores various aspects of software creation and development as well as data and information processing. It covers relevant topics such as business analysis, business rules, requirements engineering, software development processes, software defect prediction, information management systems, and knowledge management solutions. Lastly, the book presents lessons learned in information and data management processes and procedures.
Data Classification: Algorithms and Applications (Chapman And Hall/crc Data Mining And Knowledge Discovery Ser. #35)
by Charu C. AggarwalComprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi
Data Clustering: Algorithms and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series #31)
by Charu C. Aggarwal Chandan K. ReddyResearch on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Data Collection: Planning for and Collecting All Types of Data
by Cathy A. Stawarski Patricia Pulliam PhillipsData Collection Data Collection is the second of six books in the Measurement and Evaluation Series from Pfeiffer. The proven ROI Methodology--developed by the ROI Institute--provides a practical system for evaluation planning, data collection, data analysis, and reporting. All six books in the series offer the latest tools, most current research, and practical advice for measuring ROI in a variety of settings. Data Collection offers an effective process for collecting data that is essential to the implementation of the ROI Methodology. The authors outline the techniques, processes, and critical issues involved in successful data collection. The book examines the various methods of data collection, including questionnaires, interviews, focus groups, observation, action plans, performance contracts, and monitoring records. Written for evaluators, facilitators, analysts, designers, coordinators, and managers, Data Collection is a valuable guide for collecting data that are adequate in quantity and quality to produce a complete and credible analysis.
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.