Big data positivism’s quantitative methodology disregards the qualitative aspects of the analysis of society, such as ethics, morals, critique, theory, emotions, affects, motivations, worldviews, interpretations, political assessments, power, social struggles, or contradictions. The danger is that big data analytics advances uncritical, instrumental knowledge that serves dominant interests in the execution of capitalist rule and domination. Another danger of big data analytics is that the social sciences and humanities are colonised by a combination of computer science and business studies that tries to root out critical thinking and critical theory by instrumental big data reason. Big data analytics is one of the newest developments in the history of tools of reification that Lukács analyses and criticises.
Chen et al.’s (2012) article is one of the most cited articles that contain “big data” in the title<sup>7</sup>. The authors identify big data analytics as “business intelligence and analytics (BI&A) 3.0” that follows after the two stages of BI&A 1.0 (statistical analysis and data mining applied to structured data collected through enterprise systems) and BI&A 2.0 (text and web analytics applied to unstructured web contents).
[B]ig data and big data analytics have been used to describe the data sets and analytical techniques in applications that are so large (from terabytes to exabytes) and complex (from sensor to social media data) that they require advanced and unique data storage, management, analysis, and visualization technologies. (Chen et al. 2012, 1166)
The authors argue that big data analytics will have “big impact” (Chen et al. 2012, 1168) on society. They list purely positive impacts in the realms of the economy, politics, science and technology, health and wellbeing, and security and public safety that include “increased sale and customer satisfaction”, the improvement of “transparency, participation, and equality”, increased “scientific impact”, “[i]mproved healthcare quality”, and “[i]mproved public safety and security”. Chen, Chiang, and Story’s article is typical for mainstream research on big data: it is the expression of highly reified thought that argues that pure quantification as represented by big data analytics will radically transform society and only have positive impacts that will improve life in society in many respects. Possible negative consequences are not analysed and discussed, which is the consequence of the abstraction of the analysis from society as totality and its social relations of power.
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7 ISI Web of Knowledge: search conducted on July 29, 2018: With 863 citations, the article was the second most cited work containing “big data” in the title.