Inflated granularity: Spatial “Big Data” and geodemographics

• Published in: Big data & society Vol. 2; no. 2
• Main Authors: Dalton, Craig M, Thatcher, Jim
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 27.08.2015; SAGE Publishing
• Subjects: Big Data; data analytics; black box; data science; geodemographics; critical data studies
• ISSN: 2053-9517; 2053-9517
• DOI: 10.1177/2053951715601144

Data analytics, particularly the current rhetoric around “Big Data”, tend to be presented as new and innovative, emerging ahistorically to revolutionize modern life. In this article, we situate one branch of Big Data analytics, spatial Big Data, through a historical predecessor, geodemographic analysis, to help develop a critical approach to current data analytics. Spatial Big Data promises an epistemic break in marketing, a leap from targeting geodemographic areas to targeting individuals. Yet it inherits characteristics and problems from geodemographics, including a justification through the market, and a process of commodification through the black-boxing of technology. As researchers develop sustained critiques of data analytics and its effects on everyday life, we must so with a grounding in the cultural and historical contexts from which data technologies emerged. This article and others (Barnes and Wilson, 2014) develop a historically situated, critical approach to spatial Big Data. This history illustrates connections to the critical issues of surveillance, redlining, and the production of consumer subjects and geographies. The shared histories and structural logics of spatial Big Data and geodemographics create the space for a continued critique of data analyses’ role in society.