Big Data

Potential, Challenges and Statistical Implications

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.
Publication date: September 2017
ISBN: 9781484310908
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Topics covered in this book

This title contains information about the following subjects. Click on a subject if you would like to see other titles with the same subjects.

Big Data , Macroeconomic and Financial Statistics , Official Statistics , Data Quality , General , Institutions and the Macroeconomy , Introductory Material

Summary