Cover Staff Discussion Notes
Big Data: Potential, Challenges and Statistical Implications
Author:
Cornelia Hammernull

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,
Ms. Diane C Kostroch
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Mr. Gabriel Quiros-Romero
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Series:
Staff Discussion Notes
Volume/Issue:
Volume 2017: Issue 006
Language:
English
Publication Date:
13 Sep 2017
DOI:
https://doi.org/10.5089/9781484310908.006
ISBN:
9781484310908
ISSN:
2617-6750
Pages:
41
Keywords:
SDN; big data data source; strategy action plan; innovation challenge; big data application; big data classification; big data project; IMF big data; private sector; project inventory; Big Data; Macroeconomic and Financial Statistics; Official Statistics; Data Quality; Surveillance; statistics big data strategy action plan; big data data analysis; big data network; big data revolution; big data use; Social networks; Financial statistics; Global
Legal-disclaimer:
Staff Discussion Notes (SDNs) showcase policy-related analysis and research being developed by IMF staff members and are published to elicit comments and to encourage debate.The views expressed in this Policy Discussion Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy.
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Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward.
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Cover Staff Discussion Notes
Staff Discussion Notes
ISSN:
2617-6750
Publisher:
International Monetary Fund
Volume 2017: Issue 006