Quotation Hackl, Peter. 2016. Big Data: What can official statistics expect? Statistical Journal of the IAOS. 32 43-52.


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Abstract

New data sources are becoming available, in particular as a consequence of the enormously growing use of electronic media. These new data sources, often called the Big Data, open new opportunities for official statistics: Statistical products may be delivered in shorter time, with more detailed breakdowns, at lesser costs, and with reduced response burden. The paper gives a short overview of Big Data pilots and projects conducted in official statistics at national and international levels. The experiences from these projects in using the new data sources indicate that there is no uniform methodological approach for using the new data in the various statistical domains nor to take advantage of the new opportunities. Official statistics cannot expect that Big Data will substitute actual data sources like data from surveys and administration, but they may play a role as supplements for existing data in the production of certain statistics. A number of challenges are involved in using Big Data in official statistics: Solutions for methodological and technological issues are needed, a quality framework must be developed, and the staff has to get acquainted with new skills. Further issues concern the statistical environment such as legislative requirements, costs of sourcing of Big Data, and privacy, and have only indirectly to do with the statistical production. Finding solutions for these issues and developing standards that will be accepted internationally may require substantial efforts and take some time.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Statistical Journal of the IAOS
WU-Journal-Rating new VW-D
Language English
Title Big Data: What can official statistics expect?
Volume 32
Year 2016
Page from 43
Page to 52
Reviewed? Y
DOI https://doi.org/10.3233/SJI-160965
Open Access N

Associations

People
Hackl, Peter (Former researcher)
Organization
Finance, Accounting and Statistics DP (Details)
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