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This Supplement describes how the staff proposes to achieve further synergies by mapping the DQAF into the metadata structure of the DQP’s other key component: (3) the data transparency initiatives comprising the Special Data Dissemination Standard (SDDS) and General Data Dissemination System (GDDS).
Book Synopsis Sixth Review of the Fund's Data Standards Initiatives - Metadata Standardization in the Data Quality Program by : International Monetary Fund. Statistics Dept.
Download or read book Sixth Review of the Fund's Data Standards Initiatives - Metadata Standardization in the Data Quality Program written by International Monetary Fund. Statistics Dept. and published by International Monetary Fund. This book was released on 2005-01-07 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Supplement describes how the staff proposes to achieve further synergies by mapping the DQAF into the metadata structure of the DQP’s other key component: (3) the data transparency initiatives comprising the Special Data Dissemination Standard (SDDS) and General Data Dissemination System (GDDS).
The Data Standards Initiatives, the SDDS and the GDDS, have achieved the goals the Executive Board set in its Fifth Review of July 2003. The staff sees the next three years as a period of consolidating these gains by maintaining the credibility of the SDDS through improved monitoring of countries’ observance of its requirements, and further integrating both the SDDS and GDDS under the Fund’s Data Quality Program (DQP) by aligning their structure with the Fund’s Data Quality Assessment Framework (DQAF). The staff proposes to include no new data categories in the SDDS and GDDS. Instead, the staff proposes to deepen descriptive information on how countries cover oil and gas activities and products in selected existing data categories.
Book Synopsis Sixth Review of the Fund's Data Standards Initiatives by : International Monetary Fund. Statistics Dept.
Download or read book Sixth Review of the Fund's Data Standards Initiatives written by International Monetary Fund. Statistics Dept. and published by International Monetary Fund. This book was released on 2005-01-07 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Data Standards Initiatives, the SDDS and the GDDS, have achieved the goals the Executive Board set in its Fifth Review of July 2003. The staff sees the next three years as a period of consolidating these gains by maintaining the credibility of the SDDS through improved monitoring of countries’ observance of its requirements, and further integrating both the SDDS and GDDS under the Fund’s Data Quality Program (DQP) by aligning their structure with the Fund’s Data Quality Assessment Framework (DQAF). The staff proposes to include no new data categories in the SDDS and GDDS. Instead, the staff proposes to deepen descriptive information on how countries cover oil and gas activities and products in selected existing data categories.
The IMF's work on data dissemination standards consists of two tiers: the General Data Dissemination System (GDDS), which applies to all IMF member countries, and the Special Data Dissemination Standard (SDDS), for those members having or seeking access to international capital markets. The GDDS framework provide governments with guidance on the overall development of the macroeconomic, financial, and sociodemographic data that are essential for policymaking and analysis in an environment that increasingly requires relevant, comprehensive, and accurate statistical data. This Guide explains the nature, objectives, and operation of the GDDS; the data dimensions it covers; and how countries participate. It provides national statistical authorities with a management tool and a framework to foster sound statistical methodology, professional data compilation, and data dissemination. The Guide supersedes the version updated in March 2002 and incorporates the UN Millennium Development Goals (MDGs) as specific elements of the GDDS sociodemographic component, which was articulated with the collaboration of the World Bank.
Book Synopsis The General Data Dissemination System by : International Monetary Fund
Download or read book The General Data Dissemination System written by International Monetary Fund and published by International Monetary Fund. This book was released on 2007-07-25 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: The IMF's work on data dissemination standards consists of two tiers: the General Data Dissemination System (GDDS), which applies to all IMF member countries, and the Special Data Dissemination Standard (SDDS), for those members having or seeking access to international capital markets. The GDDS framework provide governments with guidance on the overall development of the macroeconomic, financial, and sociodemographic data that are essential for policymaking and analysis in an environment that increasingly requires relevant, comprehensive, and accurate statistical data. This Guide explains the nature, objectives, and operation of the GDDS; the data dimensions it covers; and how countries participate. It provides national statistical authorities with a management tool and a framework to foster sound statistical methodology, professional data compilation, and data dissemination. The Guide supersedes the version updated in March 2002 and incorporates the UN Millennium Development Goals (MDGs) as specific elements of the GDDS sociodemographic component, which was articulated with the collaboration of the World Bank.
Book Synopsis Second Review of the Special Data Dissemination Standard by : International Monetary Fund. Statistics Dept.
Download or read book Second Review of the Special Data Dissemination Standard written by International Monetary Fund. Statistics Dept. and published by International Monetary Fund. This book was released on 1998-02-12 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: NULL
The International Monetary Fund (IMF) launched the data standards initiatives to enhance member countries’ data transparency and to promote their development of sound statistical systems. The need for data standards was highlighted by the financial crises of the mid-1990s, in which information deficiencies were seen to play a role. Under the data standards initiatives, the IMF established the Special Data Dissemination Standard (SDDS) in 1996 to provide guidance to countries that have or seek access to capital markets to disseminate key data so that users in general, and financial market participants in particular, have adequate information to assess the economic situations of individual countries. The SDDS not only prescribes that subscribers disseminate certain data categories, but also prescribes that subscribers disseminate the relevant metadata to promote public knowledge and understanding of their compilation practices with respect to the required data categories. In 1997, the IMF introduced under the initiatives the General Data Dissemination System (GDDS) to provide a framework for countries that aim to develop their statistical systems, within which they can work toward disseminating comprehensive and reliable data and, eventually, meet SDDS requirements. At the Eighth Review of the Fund’s Data Standards Initiatives in February 2012, the IMF’s Executive Board approved the SDDS Plus as an upper tier of the Fund’s data standards initiatives. The SDDS Plus is open to all SDDS subscribers and is aimed at economies with systemically important financial sectors.
Book Synopsis The Special Data Dissemination Standard by : International Monetary Fund. Statistics Dept.
Download or read book The Special Data Dissemination Standard written by International Monetary Fund. Statistics Dept. and published by International Monetary Fund. This book was released on 2014-01-07 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Monetary Fund (IMF) launched the data standards initiatives to enhance member countries’ data transparency and to promote their development of sound statistical systems. The need for data standards was highlighted by the financial crises of the mid-1990s, in which information deficiencies were seen to play a role. Under the data standards initiatives, the IMF established the Special Data Dissemination Standard (SDDS) in 1996 to provide guidance to countries that have or seek access to capital markets to disseminate key data so that users in general, and financial market participants in particular, have adequate information to assess the economic situations of individual countries. The SDDS not only prescribes that subscribers disseminate certain data categories, but also prescribes that subscribers disseminate the relevant metadata to promote public knowledge and understanding of their compilation practices with respect to the required data categories. In 1997, the IMF introduced under the initiatives the General Data Dissemination System (GDDS) to provide a framework for countries that aim to develop their statistical systems, within which they can work toward disseminating comprehensive and reliable data and, eventually, meet SDDS requirements. At the Eighth Review of the Fund’s Data Standards Initiatives in February 2012, the IMF’s Executive Board approved the SDDS Plus as an upper tier of the Fund’s data standards initiatives. The SDDS Plus is open to all SDDS subscribers and is aimed at economies with systemically important financial sectors.
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
Book Synopsis The Elements of Big Data Value by : Edward Curry
Download or read book The Elements of Big Data Value written by Edward Curry and published by Springer Nature. This book was released on 2021-08-01 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
The fourth review of a three-year Extended Credit Facility (ECF) arrangement (SDR 324 million, 200 percent of quota) was concluded on December 20, 2023. Economic growth momentum softened in 2023 as oil production surprised on the downside, which, together with the 2023-2024 floods, challenges in the provisioning of electricity, and weaker public investment, weighed on non-hydrocarbon growth as well. Growth is expected to recover to close to 4 percent over the medium term. Under-execution of public spending across the board, but particularly on capital expenditures and social transfers, brought the 2023 non-hydrocarbon primary deficit to 8.4 percent of non-hydrocarbon GDP, which is 3.2 percentage points lower than projected in the fourth review (CR 24/2). However, the current account weakened, a trend that is projected to continue over the medium term, as oil production stagnates while oil prices are slightly trending down. Despite external arrears remaining below the de-minimis threshold, public debt is assessed as sustainable but “in distress” due to frequent accumulation of new external arrears and lingering uncertainty about the size of domestic arrears.
Book Synopsis Republic of Congo by : International Monetary Fund. African Dept.
Download or read book Republic of Congo written by International Monetary Fund. African Dept. and published by International Monetary Fund. This book was released on 2024-07-29 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth review of a three-year Extended Credit Facility (ECF) arrangement (SDR 324 million, 200 percent of quota) was concluded on December 20, 2023. Economic growth momentum softened in 2023 as oil production surprised on the downside, which, together with the 2023-2024 floods, challenges in the provisioning of electricity, and weaker public investment, weighed on non-hydrocarbon growth as well. Growth is expected to recover to close to 4 percent over the medium term. Under-execution of public spending across the board, but particularly on capital expenditures and social transfers, brought the 2023 non-hydrocarbon primary deficit to 8.4 percent of non-hydrocarbon GDP, which is 3.2 percentage points lower than projected in the fourth review (CR 24/2). However, the current account weakened, a trend that is projected to continue over the medium term, as oil production stagnates while oil prices are slightly trending down. Despite external arrears remaining below the de-minimis threshold, public debt is assessed as sustainable but “in distress” due to frequent accumulation of new external arrears and lingering uncertainty about the size of domestic arrears.
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
Book Synopsis Registries for Evaluating Patient Outcomes by : Agency for Healthcare Research and Quality/AHRQ
Download or read book Registries for Evaluating Patient Outcomes written by Agency for Healthcare Research and Quality/AHRQ and published by Government Printing Office. This book was released on 2014-04-01 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
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.
Book Synopsis The Practitioner's Guide to Data Quality Improvement by : David Loshin
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.
What do you know about your data? And how do you know what you know about your data? Information governance initiatives address corporate concerns about the quality and reliability of information in planning and decision-making processes. Metadata management refers to the tools, processes, and environment that are provided so that organizations can reliably and easily share, locate, and retrieve information from these systems. Enterprise-wide information integration projects integrate data from these systems to one location to generate required reports and analysis. During this type of implementation process, metadata management must be provided along each step to ensure that the final reports and analysis are from the right data sources, are complete, and have quality. This IBM® Redbooks® publication introduces the information governance initiative and highlights the immediate needs for metadata management. It explains how IBM InfoSphereTM Information Server provides a single unified platform and a collection of product modules and components so that organizations can understand, cleanse, transform, and deliver trustworthy and context-rich information. It describes a typical implementation process. It explains how InfoSphere Information Server provides the functions that are required to implement such a solution and, more importantly, to achieve metadata management. This book is for business leaders and IT architects with an overview of metadata management in information integration solution space. It also provides key technical details that IT professionals can use in a solution planning, design, and implementation process.
Book Synopsis Metadata Management with IBM InfoSphere Information Server by : Wei-Dong Zhu
Download or read book Metadata Management with IBM InfoSphere Information Server written by Wei-Dong Zhu and published by IBM Redbooks. This book was released on 2011-10-18 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: What do you know about your data? And how do you know what you know about your data? Information governance initiatives address corporate concerns about the quality and reliability of information in planning and decision-making processes. Metadata management refers to the tools, processes, and environment that are provided so that organizations can reliably and easily share, locate, and retrieve information from these systems. Enterprise-wide information integration projects integrate data from these systems to one location to generate required reports and analysis. During this type of implementation process, metadata management must be provided along each step to ensure that the final reports and analysis are from the right data sources, are complete, and have quality. This IBM® Redbooks® publication introduces the information governance initiative and highlights the immediate needs for metadata management. It explains how IBM InfoSphereTM Information Server provides a single unified platform and a collection of product modules and components so that organizations can understand, cleanse, transform, and deliver trustworthy and context-rich information. It describes a typical implementation process. It explains how InfoSphere Information Server provides the functions that are required to implement such a solution and, more importantly, to achieve metadata management. This book is for business leaders and IT architects with an overview of metadata management in information integration solution space. It also provides key technical details that IT professionals can use in a solution planning, design, and implementation process.
