Download or read book Calidad de Datos written by Mario G. Piattini Velthuis and published by Grupo Editorial RA-MA. This book was released on with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: En la actualidad los datos han cobrado una importancia esencial en las organizaciones que se están transformando digitalmente y convirtiéndose en data centric para poder ofrecer un servicio de excelencia a todos sus stakeholders y tomar las mejores decisiones. En efecto, los avances tecnológicos que estamos viviendo en los últimos años, que nos permiten recoger y almacenar enormes cantidades de datos (por medio de dispositivos móviles, sensores, Internet de las cosas, big data, etc.), tratarlos mediante diferentes algoritmos analíticos avanzados (machine learning, business intelligence, etc) , y disponer de una prácticamente ilimitada cantidad de procesamiento (en forma de servicio, mediante la computación en la nube), han convertido los datos en el “nuevo petróleo del siglo XXI”. Pero para que los datos sean el activo más importante de las organizaciones, debe tener la “calidad” adecuada; ya que los resultados de cualquier algoritmo y de cualquier decisión que se tome, no será mejor que los datos sobre los que se basa. Esta obra reúne varios aspectos relacionados con la calidad de los datos, ofreciendo una amplia visión sobre diferentes factores (especialmente técnicas, modelos y procesos) que se deben tener en consideración para la gestión, calidad y gobierno de los datos y de la información. A lo largo de esta obra se ha combinado el rigor científico con la experiencia práctica adquirida durante más de veinte años en investigación y en proyectos empresariales. Como señala Carlos Manuel Fernández en el prólogo, “este es un libro que es pionero a nivel internacional, pues sirve de guía para conseguir que las organizaciones puedan lograr smart data como activo principal y cumplir con sus objetivos ya sean de negocio o de servicio público”.

Download or read book Calidad de Datos written by Mario G. Piattini Velthuis and published by Ra-Ma Editorial. This book was released on 2018-07-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: En la actualidad los datos han cobrado una importancia esencial en las organizaciones que se están transformando digitalmente y convirtiéndose en data centric para poder ofrecer un servicio de excelencia a todos sus stakeholders y tomar las mejores decisiones. En efecto, los avances tecnológicos que estamos viviendo en los últimos años, que nos permiten recoger y almacenar enormes cantidades de datos (por medio de dispositivos móviles, sensores, Internet de las cosas, big data, etc.), tratarlos mediante diferentes algoritmos analíticos avanzados (machine learning, business intelligence, etc) , y disponer de una prácticamente ilimitada cantidad de procesamiento (en forma de servicio, mediante la computación en la nube), han convertido los datos en el “nuevo petróleo del siglo XXI”. Pero para que los datos sean el activo más importante de las organizaciones, debe tener la “calidad” adecuada; ya que los resultados de cualquier algoritmo y de cualquier decisión que se tome, no será mejor que los datos sobre los que se basa. Esta obra reúne varios aspectos relacionados con la calidad de los datos, ofreciendo una amplia visión sobre diferentes factores (especialmente técnicas, modelos y procesos) que se deben tener en consideración para la gestión, calidad y gobierno de los datos y de la información. A lo largo de esta obra se ha combinado el rigor científico con la experiencia práctica adquirida durante más de veinte años en investigación y en proyectos empresariales. Como señala Carlos Manuel Fernández en el prólogo, “este es un libro que es pionero a nivel internacional, pues sirve de guía para conseguir que las organizaciones puedan lograr smart data como activo principal y cumplir con sus objetivos ya sean de negocio o de servicio público”.

Download or read book Calidad de los datos estadisticos written by S. S. Zarkovich and published by . This book was released on 1968 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Data Quality written by Shazia Sadiq and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.

Download or read book Data Quality written by Organización Internacional de Normalización and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: La familia ISO 8000 está compuesta por 4 partes principales: conceptos generales sobre calidad de datos (partes 1, 2 y 8), procesos de gestión de calidad de datos (partes 6x), aspectos de intercambio de datos maestros entre organizaciones, atendiendo a ciertos aspectos de calidad (partes 100 a 150) e información de ingeniería (parte 311). Las partes de ISO 8000 relacionadas con la gestión de calidad de datos se centran en los procesos de gestión de calidad de datos de una organización sometidos a un ciclo de mejora continua. En la parte ISO 8000-61 se especifican los procesos requeridos para la gestión de calidad en un modelo de referencia.

Download or read book Data Quality written by Organización Internacional de Normalización and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: La familia ISO 8000 está compuesta por 4 partes principales: conceptos generales sobre calidad de datos (partes 1, 2 y 8), procesos de gestión de calidad de datos (partes 6x), aspectos de intercambio de datos maestros entre organizaciones, atendiendo a ciertos aspectos de calidad (partes 100 a 150) e información de ingeniería (parte 311). La parte ISO 8000-130 establece cómo añadir información a los mensajes de datos maestros sobre el grado de precisión que tienen los datos.

Download or read book Management Information Systems written by Kenneth C. Laudon and published by Pearson Educación. This book was released on 2004 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Management Information Systems provides comprehensive and integrative coverage of essential new technologies, information system applications, and their impact on business models and managerial decision-making in an exciting and interactive manner. The twelfth edition focuses on the major changes that have been made in information technology over the past two years, and includes new opening, closing, and Interactive Session cases.

Download or read book Data Quality written by Organización Internacional de Normalización and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: La familia ISO 8000 está compuesta por 4 partes principales: conceptos generales sobre calidad de datos (partes 1, 2 y 8), procesos de gestión de calidad de datos (partes 6x), aspectos de intercambio de datos maestros entre organizaciones, atendiendo a ciertos aspectos de calidad (partes 100 a 150) e información de ingeniería (parte 311).La parte ISO 8000-140 establece cómo añadir información sobre el grado de completitud que tienen los datos que están siendo intercambiados.

Download or read book Data Quality for the Information Age written by Thomas C. Redman and published by Artech House Publishers. This book was released on 1996 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: All aspects of data management are explored in this title, which provides detailed analyses of quality problems and their impacts, potential solutions and how they are combined to form an overall data quality program, senior management's role, and methods used to make and sustain improvements.

Download or read book Data Quality written by Organización Internacional de Normalización and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: La familia ISO 8000 está compuesta por 4 partes principales: conceptos generales sobre calidad de datos (partes 1, 2 y 8), procesos de gestión de calidad de datos (partes 6x), aspectos de intercambio de datos maestros entre organizaciones, atendiendo a ciertos aspectos de calidad (partes 100 a 150) e información de ingeniería (parte 311). La ISO 8000-150 especifica los principios fundamentales de la gestión de la calidad de los datos maestros.

Download or read book Global Entrepreneurship Analytics written by Milenka Linneth Argote Cusi and published by Routledge. This book was released on 2020-09-20 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative book proposes new methodologies for the measurement of entrepreneurship by applying techniques of demography, engineering, mathematics and statistics. Using the data from the Global Entrepreneurship Monitor (GEM), statistical demographic techniques are used for the evaluation of data quality (EDQ), and a new methodology for the estimation of Specific Entrepreneurship Rates (SER) and the Global Entrepreneurship Rate (GER) is proposed. At the same time the authors present artificial intelligence techniques such as Fuzzy Time Series (FTS) to forecast data series of the entrepreneurial population. Finally, they present a case study of the implementation of Big Data in Entrepreneurship using GEM data that shows the latest technological trends for the management of data, in support of making more accurate decisions. Being a methodological book, the techniques presented can be applied to any dataset in different areas. Readers will learn new methodologies of analysis and measurement of entrepreneurship using data from the Global Entrepreneurship Monitor. They will be able to access the experience of the authors through each of the applied cases in which the reader is taken by the hand, both through the scientific method and through the methodology of construction of more accurate metrics in entrepreneurship, with less error. This book will be of value to students at an advanced level, academics and researchers in the fields of Entrepreneurship, Business Analytics and Research Methodology.

Download or read book Data Quality written by Rupa Mahanti and published by . This book was released on 2018 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Executing Data Quality Projects written by Danette McGilvray and published by Academic Press. This book was released on 2021-05-27 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today’s data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization’s standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach Contains real examples from around the world, gleaned from the author’s consulting practice and from those who implemented based on her training courses and the earlier edition of the book Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online

Download or read book Big data written by Patricia Fernández, Eva (coord.) and published by Editorial UOC. This book was released on 2017-02-27 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: El big data, entendido como la gestión y el almacenamiento masivo de datos, es una tendencia por explotar a día de hoy. La industria audiovisual, consciente de ello, empieza a orientar estrategias de negocio con ideas de personalización de contenidos, segmentación de perfiles o predicción de tendencias. Comprender todas las posibilidades que nos ofrece el big data supone entender las dinámicas internas del negocio, así como las fuentes de datos de las que podemos extraer información y la interacción que podemos realizar con ellas. Y también nos permite formular mejores preguntas y tomar decisiones acertadas. Este libro ofrece un recorrido por el proceso de gestión de datos en la empresa, con introducción de explicaciones técnicas y especial atención a la toma de decisiones del business intelligence.

Download or read book Data and Information Quality written by Carlo Batini and published by Springer. This book was released on 2016-03-23 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.

Download or read book Data Governance written by Ismael Caballero and published by Springer Nature. This book was released on 2024-01-28 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a set of models, methods, and techniques that allow the successful implementation of data governance (DG) in an organization and reports real experiences of data governance in different public and private sectors. To this end, this book is composed of two parts. Part I on “Data Governance Fundamentals” begins with an introduction to the concept of data governance that stresses that DG is not primarily focused on databases, clouds, or other technologies, but that the DG framework must be understood by business users, systems personnel, and the systems themselves alike. Next, chapter 2 addresses crucial topics for DG, such as the evolution of data management in organizations, data strategy and policies, and defensive and offensive approaches to data strategy. Chapter 3 then details the central role that human resources play in DG, analysing the key responsibilities of the different DG-related roles and boards, while chapter 4 discusses the most common barriers to DG in practice. Chapter 5 summarizes the paradigm shifts in DG from control to value creation. Subsequently chapter 6 explores the needs, characteristics and key functionalities of DG tools, before this part ends with a chapter on maturity models for data governance. Part II on “Data Governance Applied” consists of five chapters which review the situation of DG in different sectors and industries. Details about DG in the banking sector, public administration, insurance companies, healthcare and telecommunications each are presented in one chapter. The book is aimed at academics, researchers and practitioners (especially CIOs, Data Governors, or Data Stewards) involved in DG. It can also serve as a reference for courses on data governance in information systems.

Download or read book The Practitioner s Guide to Data Quality Improvement written by David Loshin and published by Elsevier. This book was released on 2010-11-22 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.