Sixth Review of the Fund's Data Standards Initiatives - Metadata Standardization in the Data Quality Program PDF Download

Author: International Monetary Fund. Statistics Dept.
Publisher: International Monetary Fund
ISBN: 1498331408
Category : Computers
Languages : en
Pages : 16

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Book Description
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).

Author: International Monetary Fund. Statistics Dept.
Publisher: International Monetary Fund
ISBN: 1498331459
Category : Computers
Languages : en
Pages : 53

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Book Description
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.

Author: International Monetary Fund. Statistics Dept.
Publisher: International Monetary Fund
ISBN: 1616359811
Category : Computers
Languages : en
Pages : 111

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Book Description
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.

Author: Edward Curry
Publisher: Springer Nature
ISBN: 3030681769
Category : Computers
Languages : en
Pages : 399

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Book Description
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.

Author: Agency for Healthcare Research and Quality/AHRQ
Publisher: Government Printing Office
ISBN: 1587634333
Category : Medical
Languages : en
Pages : 385

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Book Description
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.

Author: Wei-Dong Zhu
Publisher: IBM Redbooks
ISBN: 0738435996
Category : Computers
Languages : en
Pages : 458

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Book Description
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.

Author: David Loshin
Publisher: Elsevier
ISBN: 0080920349
Category : Computers
Languages : en
Pages : 423

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Book Description
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.

Author: International Monetary Fund. African Dept.
Publisher: International Monetary Fund
ISBN:
Category :
Languages : en
Pages : 155

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Book Description
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.

Author: El Bachir Boukherouaa
Publisher: International Monetary Fund
ISBN: 1589063953
Category : Business & Economics
Languages : en
Pages : 35

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Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Author: Chuck Ballard
Publisher: IBM Redbooks
ISBN: 0738439517
Category : Computers
Languages : en
Pages : 264

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Book Description
Managing information within the enterprise has always been a vital and important task to support the day-to-day business operations and to enable analysis of that data for decision making to better manage and grow the business for improved profitability. To do all that, clearly the data must be accurate and organized so it is accessible and understandable to all who need it. That task has grown in importance as the volume of enterprise data has been growing significantly (analyst estimates of 40 - 50% growth per year are not uncommon) over the years. However, most of that data has been what we call "structured" data, which is the type that can fit neatly into rows and columns and be more easily analyzed. Now we are in the era of "big data." This significantly increases the volume of data available, but it is in a form called "unstructured" data. That is, data from sources that are not as easily organized, such as data from emails, spreadsheets, sensors, video, audio, and social media sites. There is valuable information in all that data but it calls for new processes to enable it to be analyzed. All this has brought with it a renewed and critical need to manage and organize that data with clarity of meaning, understandability, and interoperability. That is, you must be able to integrate this data when it is from within an enterprise but also importantly when it is from many different external sources. What is described here has been and is being done to varying extents. It is called "information governance." Governing this information however has proven to be challenging. But without governance, much of the data can be less useful and perhaps even used incorrectly, significantly impacting enterprise decision making. So we must also respect the needs for information security, consistency, and validity or else suffer the potential economic and legal consequences. Implementing sound governance practices needs to be an integral part of the information control in our organizations. This IBM® Redbooks® publication focuses on the building blocks of a solid governance program. It examines some familiar governance initiative scenarios, identifying how they underpin key governance initiatives, such as Master Data Management, Quality Management, Security and Privacy, and Information Lifecycle Management. IBM Information Management and Governance solutions provide a comprehensive suite to help organizations better understand and build their governance solutions. The book also identifies new and innovative approaches that are developed by IBM practice leaders that can help as you implement the foundation capabilities in your organizations.