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| data governance case study examples: Data Governance Dimitrios Sargiotis, |
| data governance case study examples: Data Integrity and Data Governance R. D. McDowall, 2018-11-09 This book provides practical and detailed advice on how to implement data governance and data integrity for regulated analytical laboratories working in the pharmaceutical and allied industries. |
| data governance case study examples: Data Quality Jack E. Olson, 2003-01-09 Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets. |
| data governance case study examples: Data Analysis for Business, Economics, and Policy Gábor Békés, Gábor Kézdi, 2021-05-06 A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data. |
| data governance case study examples: DAMA-DMBOK Dama International, 2017 Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment. |
| data governance case study examples: Data Governance John Ladley, 2019-11-08 Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition |
| data governance case study examples: The Data Governance Imperative Steve Sarsfield, 2009-04-23 This practical book covers both strategies and tactics around managing a data governance initiative to help make the most of your data. |
| data governance case study examples: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness. |
| data governance case study examples: Data Governance Success Rupa Mahanti, 2021-12-13 While good data is an enterprise asset, bad data is an enterprise liability. Data governance enables you to effectively and proactively manage data assets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot confusion around what data governance is, and a lot of challenges in the implementation of data governance. Data governance is not a project or a one-off exercise but a journey that involves a significant amount of effort, time and investment and cultural change and a number of factors to take into consideration to achieve and sustain data governance success. Data Governance Success: Growing and Sustaining Data Governance is the third and final book in the Data Governance series and discusses the following: • Data governance perceptions and challenges • Key considerations when implementing data governance to achieve and sustain success• Strategy and data governance• Different data governance maturity frameworks• Data governance – people and process elements• Data governance metrics This book shares the combined knowledge related to data and data governance that the author has gained over the years of working in different industrial and research programs and projects associated with data, processes, and technologies and unique perspectives of Thought Leaders and Data Experts through Interviews conducted. This book will be highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge to support and succeed in data governance implementations. This book is technology agnostic and contains a balance of concepts and examples and illustrations making it easy for the readers to understand and relate to their own specific data projects. |
| data governance case study examples: Research Anthology on Privatizing and Securing Data Management Association, Information Resources, 2021-04-23 With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data. |
| data governance case study examples: Governance in the 21st Century OECD, 2001-04-27 This book explores some of the opportunities and risks - economic, social and technological - that decision-makers will have to address, and outlines what needs to be done to foster society's capacity to manage its future more flexibly and with broader participation of its citizens. |
| data governance case study examples: Educational Research and Innovation Education Governance in Action Lessons from Case Studies Burns Tracey, Köster Florian, Fuster Marc, 2016-09-09 Governing multi-level education systems requires governance models that balance responsiveness to local diversity with the ability to ensure national objectives. |
| data governance case study examples: Big Data Governance and Perspectives in Knowledge Management Strydom, Sheryl Kruger, Strydom, Moses, 2018-11-16 The world is witnessing the growth of a global movement facilitated by technology and social media. Fueled by information, this movement contains enormous potential to create more accountable, efficient, responsive, and effective governments and businesses, as well as spurring economic growth. Big Data Governance and Perspectives in Knowledge Management is a collection of innovative research on the methods and applications of applying robust processes around data, and aligning organizations and skillsets around those processes. Highlighting a range of topics including data analytics, prediction analysis, and software development, this book is ideally designed for academicians, researchers, information science professionals, software developers, computer engineers, graduate-level computer science students, policymakers, and managers seeking current research on the convergence of big data and information governance as two major trends in information management. |
| data governance case study examples: Enterprise Master Data Management Allen Dreibelbis, Eberhard Hechler, Ivan Milman, Martin Oberhofer, Paul van Run, Dan Wolfson, 2008-06-05 The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration |
| data governance case study examples: Non-Invasive Data Governance Robert S. Seiner, 2014-09-01 Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: • Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. • Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. • Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. • A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. • Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve. |
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| data governance case study examples: The Future of Open Data Pamela Robinson, Teresa Scassa, 2022-05-24 The Future of Open Data flows from a multi-year Social Sciences and Humanities Research Council (SSHRC) Partnership Grant project that set out to explore open government geospatial data from an interdisciplinary perspective. Researchers on the grant adopted a critical social science perspective grounded in the imperative that the research should be relevant to government and civil society partners in the field. This book builds on the knowledge developed during the course of the grant and asks the question, “What is the future of open data?” The contributors’ insights into the future of open data combine observations from five years of research about the Canadian open data community with a critical perspective on what could and should happen as open data efforts evolve. Each of the chapters in this book addresses different issues and each is grounded in distinct disciplinary or interdisciplinary perspectives. The opening chapter reflects on the origins of open data in Canada and how it has progressed to the present date, taking into account how the Indigenous data sovereignty movement intersects with open data. A series of chapters address some of the pitfalls and opportunities of open data and consider how the changing data context may impact sources of open data, limits on open data, and even liability for open data. Another group of chapters considers new landscapes for open data, including open data in the global South, the data priorities of local governments, and the emerging context for rural open data. |
| data governance case study examples: EJISE Volume 15 Issue 1 , |
| data governance case study examples: OECD Urban Studies Smart City Data Governance Challenges and the Way Forward OECD, 2023-10-13 Smart cities leverage technologies, in particular digital, to generate a vast amount of real-time data to inform policy- and decision-making for an efficient and effective public service delivery. Their success largely depends on the availability and effective use of data. |
| data governance case study examples: Open Data Governance and Its Actors Maxat Kassen, 2022-01-28 This book combines theoretical and practical knowledge about key actors and driving forces that help to initiate and advance open data governance. Using Finland and Sweden as case studies, it sheds light on the roles of key actors in the open data movement, enabling researchers to understand the key operational elements of data-driven governance. Examining the most salient manifestations of related networking activities, the motivations of stakeholders, and the political and socioeconomic readiness of the public, private and civic sectors to advance such policies, it will appeal to e-government experts, policymakers and political scientists, as well as academics and students of public administration, public policy, and open data governance. |
| data governance case study examples: Target-setting Methods and Data Management to Support Performance-based Resource Allocation by Transportation Agencies National Cooperative Highway Research Program, 2010 TRB's National Cooperative Highway Research Program (NCHRP) Report 666: Target Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies - Volume I: Research Report, and Volume II: Guide for Target-Setting and Data Management provides a framework and specific guidance for setting performance targets and for ensuring that appropriate data are available to support performance-based decision-making. Volume III to this report was published separately in an electronic-only format as NCHRP Web-Only Document 154. Volume III includes case studies of organizations investigated in the research used to develop NCHRP Report 666. |
| data governance case study examples: Fusing Decision Support Systems Into the Fabric of the Context Ana Respício, Frada Burstein, 2012 The field of Information Systems has been shifting from an aeimmersion viewAE, which relies on the immersion of information technology (IT) as part of the business environment, to a aefusion viewAE in which IT is fused within the business environment, forming a unified fabric that integrates work and personal life, as well as personal and public information. In the context of this fusion view, decision support systems should achieve a total alignment with the context and the personal preferences of users. The advantage of such a view is an opportunity of seamless integration between enterprise environments and decision support system components. Thus, researchers and practitioners have to address the challenges of dealing with this shift in viewpoint and its consequences for decision making and decision support systems theories and applications. This book presents the latest innovations and advances in decision support systems with a special focus on the fusion view. These achievements will be of interest to all those involved and interested in decision making practice and research, as well as, more generally, in the fusion view of modern information systems.The book covers a wide range of topical themes including a fusion view of business intelligence and data warehousing, applications of multi-criteria decision analysis, intelligent models and technologies for decision making, knowledge management, decision support approaches and models for emergency management, and medical and other specific domains. |
| data governance case study examples: Cutting-Edge Technologies for Business Sectors Ertu?rul, Duygu Çelik, Elçi, Atilla, 2024-10-17 In the rapidly evolving 21st century, emerging digital technologies are transforming every aspect of modern life, from social interactions to business practices. These advancements are reshaping industries, influencing human behavior, and redefining societal structures. Understanding the impact of technologies like AI, blockchain, and virtual reality is crucial for navigating today's digital world and its challenges. Cutting-Edge Technologies for Business Sectors provides a comprehensive look at how these innovations are revolutionizing industries such as healthcare, education, law, and tourism. By exploring the ethical, practical, and societal implications of digital tools, this volume offers valuable insights for academics, professionals, and policymakers looking to harness the power of technology and shape the future. |
| data governance case study examples: Ethical Marketing Through Data Governance Standards and Effective Technology Saluja, Shefali, Nayyar, Varun, Rojhe, Kuldeep, Sharma, Sandhir, 2024-05-13 Marketing on digital platforms requires critical thinking on data management systems, machine learning methods, and attributes like customer trust, societal ethics, and managing consumer feedback with the utmost utilization of technology in different ways. The pursuit for a unified source of information is fundamental for marketers in digital marketing. Ethical Marketing Through Data Governance Standards and Effective Technology delves into the intricacies of achieving this unity by addressing the challenges and presenting solutions in a structured manner. The book explores the fundamental necessity for an effective data governance strategy. It emphasizes the eradication of silos and the establishment of regulations governing data classification, storage, and processing. Within this framework, the application of artificial intelligence in marketing takes center stage. The book investigates Artificial Intelligence (AI) marketing, machine learning methods, and data management systems. Furthermore, the book studies advertising standards and challenges on online platforms. The intersection of technology and advertising is dissected, focusing on virtual assistance through avatars and their impact on consumer psychology. The importance of a comprehensive database governance strategy is underscored, presenting a complete approach for corporations to navigate the intricacies of online marketing while upholding ethical standards. |
| data governance case study examples: OECD Health Policy Studies Health Data Governance Privacy, Monitoring and Research OECD, 2015-10-05 This report identifies eight key data governance mechanisms to maximise benefits to patients and to societies from the collection, linkage and analysis of health data, and to minimise risks to both patient privacy and the security of health data. |
| data governance case study examples: Data Governance For Dummies Reichental, 2022-12-08 How to build and maintain strong data organizations—the Dummies way Data Governance For Dummies offers an accessible first step for decision makers into understanding how data governance works and how to apply it to an organization in a way that improves results and doesn't disrupt. Prep your organization to handle the data explosion (if you know, you know) and learn how to manage this valuable asset. Take full control of your organization’s data with all the info and how-tos you need. This book walks you through making accurate data readily available and maintaining it in a secure environment. It serves as your step-by-step guide to extracting every ounce of value from your data. Identify the impact and value of data in your business Design governance programs that fit your organization Discover and adopt tools that measure performance and need Address data needs and build a more data-centric business culture This is the perfect handbook for professionals in the world of data analysis and business intelligence, plus the people who interact with data on a daily basis. And, as always, Dummies explains things in terms anyone can understand, making it easy to learn everything you need to know. |
| data governance case study examples: One Health, Environmental Health, Global Health, and Inclusive Governance: What can we do? Ulrich Laaser, Vesna Bjegovic-Mikanovic, Richard Seifman, Flavia Senkubuge, Zeljka Stamenkovic, 2022-09-19 |
| data governance case study examples: REVOLUTIONIZING PREVENTIVE CARE AND PATIENT ENGAGEMENT: AI and Deep Learning Applications in Health Plans and Wellness RAMANAKAR REDDY DANDA, ZAKERA YASMEEN, KIRAN KUMAR MAGULURI, .. |
| data governance case study examples: Data Integration Blueprint and Modeling Anthony David Giordano, 2010-12-27 Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness Today’s enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever. This book presents the solution: a clear, consistent approach to defining, designing, and building data integration components to reduce cost, simplify management, enhance quality, and improve effectiveness. Leading IBM data management expert Tony Giordano brings together best practices for architecture, design, and methodology, and shows how to do the disciplined work of getting data integration right. Mr. Giordano begins with an overview of the “patterns” of data integration, showing how to build blueprints that smoothly handle both operational and analytic data integration. Next, he walks through the entire project lifecycle, explaining each phase, activity, task, and deliverable through a complete case study. Finally, he shows how to integrate data integration with other information management disciplines, from data governance to metadata. The book’s appendices bring together key principles, detailed models, and a complete data integration glossary. Coverage includes Implementing repeatable, efficient, and well-documented processes for integrating data Lowering costs and improving quality by eliminating unnecessary or duplicative data integrations Managing the high levels of complexity associated with integrating business and technical data Using intuitive graphical design techniques for more effective process and data integration modeling Building end-to-end data integration applications that bring together many complex data sources |
| data governance case study examples: Dimensions of Intelligent Analytics for Smart Digital Health Solutions Nilmini Wickramasinghe, Freimut Bodendorf, Mathias Kraus, 2024-03-01 This title demystifies artificial intelligence (AI) and analytics, upskilling individuals (healthcare professionals, hospital managers, consultants, researchers, students, and the population at large) around analytics and AI as it applies to healthcare. This book shows how the tools, techniques, technologies, and tactics around analytics and AI can be best leveraged and utilised to realise a healthcare value proposition of better quality, better access and high value for everyone every day, everywhere. The book presents a triumvirate approach including technical, business and medical aspects of data and analytics and by so doing takes a responsible approach to this key area. This work serves to introduce the critical issues in AI and analytics for healthcare to students, practitioners, and researchers. |
| data governance case study examples: The Peaceful Settlement of Inter-State Cyber Disputes Nicholas Tsagourias, Russell Buchan, Daniel Franchini, 2024-11-14 With cyberspace becoming a domain of inter-state conflict and confrontation, this book is one of the first studies of the ways in which international law can facilitate the peaceful settlement of inter-state cyber disputes. By employing theoretical and practical inquiries and analysis, the book examines the legal parameters of cyber dispute settlement; explores critical questions about the role of dispute settlement institutions and methods; and identifies and addresses related challenges. The book begins by considering the legal definition of a cyber dispute and the scope of the good faith obligation of states in settling their cyber disputes peacefully. It then examines the role of certain institutions (International Court of Justice, national courts, the EU, the Security Council) and methods (judicial, diplomatic, countermeasures, arbitration, conciliation, fact-finding) in the settlement of cyber disputes. It also discusses how data disputes can be settled and whether new and specialised mechanisms are needed. The book provides scholars, practitioners and law students with immediate knowledge and understanding of the role of international law in the peaceful settlement of cyber disputes, as well as how international dispute settlement as a discipline and practice can apply to this new field. |
| data governance case study examples: Big Data, Big Challenges: A Healthcare Perspective Mowafa Househ, Andre W. Kushniruk, Elizabeth M. Borycki, 2019-02-26 This is the first book to offer a comprehensive yet concise overview of the challenges and opportunities presented by the use of big data in healthcare. The respective chapters address a range of aspects: from health management to patient safety; from the human factor perspective to ethical and economic considerations, and many more. By providing a historical background on the use of big data, and critically analyzing current approaches together with issues and challenges related to their applications, the book not only sheds light on the problems entailed by big data, but also paves the way for possible solutions and future research directions. Accordingly, it offers an insightful reference guide for health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, aiding them in their decision-making processes; and for students and researchers whose work involves data science-related research issues in healthcare. |
| data governance case study examples: Data Capital Chunlei Tang, 2021-01-31 This 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 governance case study examples: Structured Worlds Jeanne Legarski, Ron Legarski, Patrick Oborn, Ned Hamzic, Steve Sramek, Bryan Clement, Patrick Leddy, Aaron Jay Lev, 2024-09-22 Structured Worlds: The Comprehensive Guide to Libraries, Directories, Categories, and the Art of Organization serves as an essential resource for anyone navigating the complexities of information management in both physical and digital environments. This guide delves deeply into the foundational principles of organization and categorization, offering practical applications across various sectors like libraries, archives, businesses, and personal data management. Covering historical approaches to organization, modern techniques, and emerging technologies, this book provides a thorough exploration of systems designed to improve data accessibility, communication, and efficiency. It addresses the challenges posed by evolving digital landscapes, offering insight into tools, software, and strategies that enhance organization, categorization, and data management. Structured in a methodical way, the book progresses from traditional organizing methods to the latest innovations, with a focus on metadata, taxonomies, artificial intelligence, and user accessibility. It is an invaluable resource for professionals, students, and enthusiasts in fields such as library science, information management, and beyond, equipping them with the knowledge to master the art of organization and data structuring for maximum efficiency. tags: organization, categorization, libraries, directories, metadata, taxonomy, digital organization, archives, information management, AI in organization, user accessibility, organizational tools, digital transformation, categorization systems, structured information |
| data governance case study examples: Federal Register , 2012-05 |
| data governance case study examples: Data Integrity and Quality Santhosh Kumar Balan, 2021-06-23 Data integrity is the quality, reliability, trustworthiness, and completeness of a data set, providing accuracy, consistency, and context. Data quality refers to the state of qualitative or quantitative pieces of information. Over five sections, this book discusses data integrity and data quality as well as their applications in various fields. |
| data governance case study examples: Secure and Intelligent IoT-Enabled Smart Cities Singh, Sushil Kumar, Tanwar, Sudeep, Jadeja, Rajendrasinh, Singh, Saurabh, Polkowski, Zdzislaw, 2024-04-01 Smart cities are experiencing a rapid evolution. The integration of technologies such as 5G, Internet of Things (IoT), Artificial Intelligence (AI), and blockchain has ushered in transformative applications, enhancing the quality of urban life. However, this evolution comes with its own challenges, most notably in security and privacy. Secure and Intelligent IoT-Enabled Smart Cities addresses these concerns, exploring theoretical frameworks and empirical research findings. The book embarks on the foundational elements of the Internet of Things, delving into the convergence of IoT and smart city applications, elucidating the layered architecture of IoT, and highlighting the security issues inherent in IoT-enabled Smart Cities. This book pinpoints the challenges smart city infrastructures face and offers innovative and pragmatic solutions to fortify their security. This book targets professionals and researchers immersed in the dynamic field of secure and intelligent environments within IoT-enabled smart city applications. It is a valuable resource for executives grappling with the strategic implications of emerging technologies in smart healthcare, smart parking, smart manufacturing, smart transportation, and beyond. |
| data governance case study examples: The Oxford Handbook of Digital Technology and Society Simeon Yates, Ronald E. Rice, 2020 The Oxford Handbook of Digital Technology and Society will equip readers with the necessary starting points and provocations in the fields of social science and technology so that students, scholars, and policy makers can effectively assess future research, practice, and policy. |
| data governance case study examples: Master Data Management David Loshin, 2010-07-28 The key to a successful MDM initiative isn't technology or methods, it's people: the stakeholders in the organization and their complex ownership of the data that the initiative will affect.Master Data Management equips you with a deeply practical, business-focused way of thinking about MDM—an understanding that will greatly enhance your ability to communicate with stakeholders and win their support. Moreover, it will help you deserve their support: you'll master all the details involved in planning and executing an MDM project that leads to measurable improvements in business productivity and effectiveness. - Presents a comprehensive roadmap that you can adapt to any MDM project - Emphasizes the critical goal of maintaining and improving data quality - Provides guidelines for determining which data to master. - Examines special issues relating to master data metadata - Considers a range of MDM architectural styles - Covers the synchronization of master data across the application infrastructure |
| data governance case study examples: Database Design, Query, Formulation, and Administration Michael Mannino, 2022-09-15 Formerly published by Chicago Business Press, now published by Sage Database Design, Query Formulation, and Administration, Eighth Edition, offers a comprehensive understanding of database technology. Author Michael Mannino equips students with the necessary tools to grasp the fundamental concepts of database management, and then guides them in honing their skills to solve both basic and advanced challenges in query formulation, data modeling, and database application development. Features of the Eighth Edition: Unmatched SQL coverage in both breadth and depth Oracle and PostgreSQL coverage Problem-solving guidelines Sample databases and examples Data modeling tools Data warehouse coverage NoSQL coverage Current and cutting-edge topics Comprehensive enough for multiple database courses |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with minimum time …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, released in …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process from …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical barriers …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be collected, …
