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Enhancing Data Management Through the Statistical Data and Metadata eXchange Standard
Enhancing Data Management Through the Statistical Data and Metadata eXchange Standard
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This publication explains how developing economies that adopt the Statistical Data and Metadata eXchange (SDMX) standard will benefit from enhanced efficiency in data collection, production, and exchange. In today's data-driven world, the efficient exchange, analysis, and dissemination of statistical data is vital for informed decision-making and policy formulation across both government and the private sector. However, the entry of new data producers and a surge in available data poses challen…
  • Leidėjas:
  • ISBN-10: 9292708155
  • ISBN-13: 9789292708153
  • Formatas: 21.6 x 27.9 x 0.6 cm, minkšti viršeliai
  • Kalba: Anglų

Enhancing Data Management Through the Statistical Data and Metadata eXchange Standard (el. knyga) (skaityta knyga) | knygos.lt

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This publication explains how developing economies that adopt the Statistical Data and Metadata eXchange (SDMX) standard will benefit from enhanced efficiency in data collection, production, and exchange.


In today's data-driven world, the efficient exchange, analysis, and dissemination of statistical data is vital for informed decision-making and policy formulation across both government and the private sector. However, the entry of new data producers and a surge in available data poses challenges for traditional statistical entities, compelling them to innovate while maintaining data quality. In response, the SDMX standard has emerged as a solution, offering a comprehensive framework to streamline data activities and promote interoperability.

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  • Leidėjas:
  • ISBN-10: 9292708155
  • ISBN-13: 9789292708153
  • Formatas: 21.6 x 27.9 x 0.6 cm, minkšti viršeliai
  • Kalba: Anglų

This publication explains how developing economies that adopt the Statistical Data and Metadata eXchange (SDMX) standard will benefit from enhanced efficiency in data collection, production, and exchange.


In today's data-driven world, the efficient exchange, analysis, and dissemination of statistical data is vital for informed decision-making and policy formulation across both government and the private sector. However, the entry of new data producers and a surge in available data poses challenges for traditional statistical entities, compelling them to innovate while maintaining data quality. In response, the SDMX standard has emerged as a solution, offering a comprehensive framework to streamline data activities and promote interoperability.

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