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The Practitioner's Guide to Data Quality Improvement

The Practitioner's Guide to Data Quality Improvement
A Book

by David Loshin

  • Publisher : Elsevier
  • Release : 2010-11-22
  • Pages : 432
  • ISBN : 9780080920344
  • Language : En, Es, Fr & De
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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.

Studyguide for the Practitioners Guide to Data Quality Improvement by Loshin, David

Studyguide for the Practitioners Guide to Data Quality Improvement by Loshin, David
A Book

by Cram101 Textbook Reviews

  • Publisher : Cram101
  • Release : 2013-05
  • Pages : 168
  • ISBN : 9781490214481
  • Language : En, Es, Fr & De
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Never HIGHLIGHT a Book Again Virtually all testable terms, concepts, persons, places, and events are included. Cram101 Textbook Outlines gives all of the outlines, highlights, notes for your textbook with optional online practice tests. Only Cram101 Outlines are Textbook Specific. Cram101 is NOT the Textbook. Accompanys: 9780521673761

Outlines and Highlights for the Practitioners Guide to Data Quality Improvement by David Loshin

Outlines and Highlights for the Practitioners Guide to Data Quality Improvement by David Loshin
A Book

by Cram101 Textbook Reviews

  • Publisher : Academic Internet Pub Incorporated
  • Release : 2011-07-01
  • Pages : 182
  • ISBN : 9781618303530
  • Language : En, Es, Fr & De
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Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780123737175 .

Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
A Data Quality Assessment Framework

by Laura Sebastian-Coleman

  • Publisher : Newnes
  • Release : 2012-12-31
  • Pages : 376
  • ISBN : 0123977541
  • Language : En, Es, Fr & De
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The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You’ll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges Enables discussions between business and IT with a non-technical vocabulary for data quality measurement Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Data Stewardship

Data Stewardship
An Actionable Guide to Effective Data Management and Data Governance

by David Plotkin

  • Publisher : Academic Press
  • Release : 2020-10-31
  • Pages : 322
  • ISBN : 0128221674
  • Language : En, Es, Fr & De
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Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data—moving from business/organizational function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered. Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/company structure, business functions, and data ownership. The book shows data managers how to gain support for a stewardship effort, maintain that support over the long-term, and measure the success of the data stewardship effort. It includes detailed lists of responsibilities for each type of data steward and strategies to help the Data Governance Program Office work effectively with the data stewards. Includes an enhanced section on data governance/stewardship structure for companies that do business internationally, including the structure of business terms to account for country differences Outlines the advantages and disadvantages of "data domains," details on suggested data domains and data domain structures, as well as data governance by data domains Integrates data governance into Project methodology, defining roles on a project, adding Data Governance tasks to the Work Breakdown Structure, as well as advantages of working closely with the Project management Office Covers the data stewardship involved in implementing national and international data privacy regulations

Data Quality

Data Quality
Dimensions, Measurement, Strategy, Management, and Governance

by Rupa Mahanti

  • Publisher : Quality Press
  • Release : 2019-03-18
  • Pages : 526
  • ISBN : 0873899776
  • Language : En, Es, Fr & De
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“This is not the kind of book that you’ll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective.” from the foreword by Thomas C. Redman, Ph.D., “the Data Doc” Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality. Specifically, the book addresses: -Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality-Butterfly effect of data quality-A detailed description of data quality dimensions and their measurement-Data quality strategy approach-Six Sigma - DMAIC approach to data quality-Data quality management techniques-Data quality in relation to data initiatives like data migration, MDM, data governance, etc.-Data quality myths, challenges, and critical success factorsStudents, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout.

Handbook of Data Quality

Handbook of Data Quality
Research and Practice

by Shazia Sadiq

  • Publisher : Springer Science & Business Media
  • Release : 2013-08-13
  • Pages : 438
  • ISBN : 3642362575
  • Language : En, Es, Fr & De
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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.

Data Quality and Trust in Big Data

Data Quality and Trust in Big Data
5th International Workshop, QUAT 2018, Held in Conjunction with WISE 2018, Dubai, UAE, November 12–15, 2018, Revised Selected Papers

by Hakim Hacid,Quan Z. Sheng,Tetsuya Yoshida,Azadeh Sarkheyli,Rui Zhou

  • Publisher : Springer
  • Release : 2019-04-24
  • Pages : 137
  • ISBN : 3030191435
  • Language : En, Es, Fr & De
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This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data and trust for Big Data.

McLaughlin & Kaluzny's Continuous Quality Improvement in Health Care

McLaughlin & Kaluzny's Continuous Quality Improvement in Health Care
A Book

by Julie K. Johnson,William A. Sollecito

  • Publisher : Jones & Bartlett Learning
  • Release : 2018-10-01
  • Pages : 650
  • ISBN : 1284126595
  • Language : En, Es, Fr & De
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Through a unique interdisciplinary perspective on quality management in health care, this text covers the subjects of operations management, organizational behavior, and health services research. With a particular focus on Total Quality Management (TQM) and Continuous Quality Improvement (CQI), the challenges of implementation and institutionalization are addressed using examples from a variety of health care organizations, including primary care clinics, hospital laboratories, public health departments, and academic health centers. Significantly revised throughout, the Fifth Edition offers a greater focus on application techniques, and features 14 chapters in lieu of the prior edition's 20 chapters, making it an even more effective teaching tool. New chapters have been incorporated on Implementation Science (3), Lean Six Sigma (6), and Classification and the Reduction of Medical Errors (10).

Building Capacity for Health Informatics in the Future

Building Capacity for Health Informatics in the Future
A Book

by F. Lau,J.A. Bartle-Clar,G. Bliss

  • Publisher : IOS Press
  • Release : 2017-03
  • Pages : 452
  • ISBN : 161499742X
  • Language : En, Es, Fr & De
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Health information technologies are revolutionizing and streamlining healthcare, and uptake continues to rise dramatically. If these technologies are to be effectively implemented, capacity must be built at a regional, national and global level, and the support and involvement of both government and industry will be vital. This book presents the proceedings of the 2017 Information Technology and Communications in Health conference (ITCH 2017), held in Victoria, BC, Canada, in February 2017. The conference considers, from a variety of perspectives, what is required to move the technology forward to real, sustained and widespread use, and the solutions examined range from improvements in usability and training to the need for new and improved design of information systems, user interfaces and interoperable solutions. Government policies, mandates, initiatives and the need for regulation are also explored, as is the requirement for improved interaction between industrial, governmental and academic partners. With its focus on building the next generation of health informatics and the capacity required to deliver better healthcare worldwide, this book will be of interest to all those involved in the provision of healthcare.

Recent Trends in Data Science and Soft Computing

Recent Trends in Data Science and Soft Computing
Proceedings of the 3rd International Conference of Reliable Information and Communication Technology (IRICT 2018)

by Faisal Saeed,Nadhmi Gazem,Fathey Mohammed,Abdelsalam Busalim

  • Publisher : Springer
  • Release : 2018-09-08
  • Pages : 1126
  • ISBN : 3319990071
  • Language : En, Es, Fr & De
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This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial Intelligence and Soft Computing, Business Intelligence, Internet of Things (IoT) Technologies and Applications, Intelligent Communication Systems, Advances in Computer Vision, Health Informatics, Reliable Cloud Computing Environments, Recent Trends in Knowledge Management, Security Issues in the Cyber World, and Advances in Information Systems Research, Theories and Methods.

Industrial Engineering and Operations Management

Industrial Engineering and Operations Management
XXVI IJCIEOM, Rio de Janeiro, Brazil, July 8–11, 2020

by Antônio Márcio Tavares Thomé,Rafael Garcia Barbastefano,Luiz Felipe Scavarda,João Carlos Gonçalves dos Reis,Marlene Paula Castro Amorim

  • Publisher : Springer Nature
  • Release : 2020-10-29
  • Pages : 649
  • ISBN : 3030569209
  • Language : En, Es, Fr & De
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This volume gathers selected peer-reviewed papers presented at the XXVI International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM), held on July 8-11, 2020 in Rio de Janeiro, Brazil. The respective chapters address a range of timely topics in industrial engineering, including operations and process management, global operations, managerial economics, data science and stochastic optimization, logistics and supply chain management, quality management, product development, strategy and organizational engineering, knowledge and information management, work and human factors, sustainability, production engineering education, healthcare operations management, disaster management, and more. These topics broadly involve fields like operations, manufacturing, industrial and production engineering, and management. Given its scope, the book offers a valuable resource for those engaged in optimization research, operations research, and practitioners alike.

Information Governance and Assurance

Information Governance and Assurance
Reducing risk, promoting policy

by Alan MacLennan

  • Publisher : Facet Publishing
  • Release : 18-06-14
  • Pages : 192
  • ISBN : 185604940X
  • Language : En, Es, Fr & De
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This comprehensive textbook discusses the legal, organizational and ethical aspects of information governance, assurance and security and their relevance to all aspects of information work. Information governance describes the activities and practices which have developed to control the use of information, including, but not limited to, practices mandated by law. In a world in which information is increasingly seen as a top-level asset, the safeguarding and management of information is of concern to everyone. From the researcher who is responsible for ethical practices in the gathering, analysis, and storage of data, to the reference librarian who must deliver unbiased information; from the records manager who must respond to information requests, to the administrator handling personnel files, this book with equip practitioners and students alike to implement good information governance practice in real-world situations. Key topics covered include: - Information as an asset - The laws and regulations - Data quality management - Dealing with threats - Security, risk management and business continuity - Frameworks, policies, ethics and how it all fits together. Readership: Fully supported by examples, discussion points and practical exercises, this is essential reading for everyone who needs to understand, implement and support information assurance policies and information governance structures. It will be particularly valuable for LIS students taking information management and information governance courses, and information professionals with an advisory or gatekeeping role in information governance within an organization.

Responsible Analytics and Data Mining in Education

Responsible Analytics and Data Mining in Education
Global Perspectives on Quality, Support, and Decision Making

by Badrul H. Khan,Joseph Rene Corbeil,Maria Elena Corbeil

  • Publisher : Routledge
  • Release : 2018-12-07
  • Pages : 292
  • ISBN : 1351394673
  • Language : En, Es, Fr & De
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Winner of two Outstanding Book Awards from the Association of Educational Communications and Technology (Culture, Learning, & Technology and Systems Thinking & Change divisions)! Rapid advancements in our ability to collect, process, and analyze massive amounts of data along with the widespread use of online and blended learning platforms have enabled educators at all levels to gain new insights into how people learn. Responsible Analytics and Data Mining in Education addresses the thoughtful and purposeful navigation, evaluation, and implementation of these emerging forms of educational data analysis. Chapter authors from around the world explore how data analytics can be used to improve course and program quality; how the data and its interpretations may inadvertently impact students, faculty, and institutions; the quality and reliability of data, as well as the accuracy of data-based decisions; ethical implications surrounding the collection, distribution, and use of student-generated data; and more. This volume unpacks and explores this complex issue through a systematic framework whose dimensions address the issues that must be considered before implementation of a new initiative or program.

Signal and Information Processing, Networking and Computers

Signal and Information Processing, Networking and Computers
Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers (ICSINC)

by Songlin Sun,Na Chen,Tao Tian

  • Publisher : Springer
  • Release : 2017-12-16
  • Pages : 511
  • ISBN : 9811075212
  • Language : En, Es, Fr & De
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This proceedings book presents the latest research in the fields of information theory, communication system, computer science and signal processing, as well as other related technologies. Collecting selected papers from the 3rd Conference on Signal and Information Processing, Networking and Computers (ICSINC), held in Chongqing, China on September 13-15, 2017, it is of interest to professionals from academia and industry alike.

Data and Information Quality

Data and Information Quality
Dimensions, Principles and Techniques

by Carlo Batini,Monica Scannapieco

  • Publisher : Springer
  • Release : 2016-03-23
  • Pages : 500
  • ISBN : 3319241060
  • Language : En, Es, Fr & De
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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.

Data Governance and Data Management

Data Governance and Data Management
Contextualizing Data Governance Drivers, Technologies, and Tools

by Rupa Mahanti

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 129
  • ISBN : 9811635838
  • Language : En, Es, Fr & De
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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXV

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXV
A Book

by Abdelkader Hameurlain,Josef Küng,Roland Wagner,Sherif Sakr,Imran Razzak,Alshammari Riyad

  • Publisher : Springer
  • Release : 2017-11-09
  • Pages : 133
  • ISBN : 3662561212
  • Language : En, Es, Fr & De
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This volume, the 35th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five fully-revised selected regular papers focusing on data quality, social-data artifacts, data privacy, predictive models, and e-health. Specifically, the five papers present and discuss a data-quality framework for the Estonian public sector; a data-driven approach to bridging the gap between the business and social worlds; privacy-preserving querying on privately encrypted data in the cloud; algorithms for the prediction of norovirus concentration in drinking water; and cloud computing in healthcare organizations in Saudi Arabia.

Business Intelligence

Business Intelligence
The Savvy Manager's Guide

by David Loshin

  • Publisher : Newnes
  • Release : 2012-11-27
  • Pages : 400
  • ISBN : 0123858909
  • Language : En, Es, Fr & De
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Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. Guides managers through developing, administering, or simply understanding business intelligence technology Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization’s data into actionable knowledge Contains a handy, quick-reference to technologies and terminology

Handbook of Research on Global Supply Chain Management

Handbook of Research on Global Supply Chain Management
A Book

by Christiansen, Bryan

  • Publisher : IGI Global
  • Release : 2015-11-12
  • Pages : 690
  • ISBN : 1466696400
  • Language : En, Es, Fr & De
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Supply Chain Management (SCM) has always been an important aspect of an enterprise’s business model and an effective supply chain network is essential to remaining competitive in a global environment. By properly managing the flow of goods and services, businesses can operate more efficiently while managing most of the workload behind-the-scenes. The Handbook of Research on Global Supply Chain Management is an in-depth reference source that covers emerging issues and relevant applications of information pertaining to supply chain management from an international perspective. Featuring coverage on topics such as the global importance of SCMs to strategies for producing an effective supply chain, this comprehensive publication is an essential resource for academics and business professionals alike interested in uncovering managerial insight and logistics solutions.