Big Data: Potential, Challenges and Statistical Implications

By Cornelia Hammer, Diane C Kostroch, Gabriel Quiros-Romero

September 13, 2017

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Cornelia Hammer, Diane C Kostroch, and Gabriel Quiros-Romero. Big Data: Potential, Challenges and Statistical Implications, (USA: International Monetary Fund, 2017) accessed December 26, 2024

Disclaimer: This Staff Discussion Note represents the views of the authors and does not necessarily represent IMF views or IMF policy. The views expressed herein should be attributed to the authors and not to the IMF, its Executive Board, or its management. Staff Discussion Notes are published to elicit comments and to further debate.

Summary

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.

Subject: Big data, Economic and financial statistics, Financial statistics, International organization, Social networks, Technology

Keywords: Big Data, Big data application, Big data classification, Big data data analysis, Big data data source, Big data network, Big data project, Big data revolution, Big data use, Data Quality, Financial statistics, Global, IMF big data, Innovation challenge, Macroeconomic and Financial Statistics, Official Statistics, Private sector, Project inventory, SDN, Social networks, Statistics big data strategy action plan, Strategy action plan, Surveillance

Publication Details

Pages:

41
Volume:

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DOI:

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Issue:

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Series:

Staff Discussion Notes No. 2017/006
Stock No:

SDNEA2017006
ISBN:

9781484310908
ISSN:

2617-6750

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