Big Data
Rospigliosi, A. 2025. Big Data. in: McCann, L., Bozkurt, Ö., Finn, R., Granter, E., Hunter, C., Kivinen, N., Kumar, A. and Wierman, B. (ed.) Elgar Encyclopedia of Critical Management Studies Chichester Edgar Elgar Publishing.
Rospigliosi, A. 2025. Big Data. in: McCann, L., Bozkurt, Ö., Finn, R., Granter, E., Hunter, C., Kivinen, N., Kumar, A. and Wierman, B. (ed.) Elgar Encyclopedia of Critical Management Studies Chichester Edgar Elgar Publishing.
| Chapter title | Big Data |
|---|---|
| Authors | Rospigliosi, A. |
| Editors | McCann, L., Bozkurt, Ö., Finn, R., Granter, E., Hunter, C., Kivinen, N., Kumar, A. and Wierman, B. |
| Abstract | Big Data is a messy concept, a phrase that attempts to capture what is different about the way statistical analysis can be done when the analyst has access to large sets of records generated by computer mediated transactions. The term ‘big’, does not only denote quantity or scale. It also indicates the nature of such datasets, where three characteristics are seen as distinct: volume, variety and velocity (Mayer-Schönberger and Cukier, 2013). While volume does mostly echo the term big, variety and velocity offer insight into the changes that the mass adoption of internet-based technologies have in capturing the detail of human communications. Sociologist Manuel Castells had already recognized in the decade in which the internet came to dominate many channels of communication, that we were witnessing the rise of the ‘network society’ (1996, 1997, 1998). The subsequent ‘big data revolution’ emphasised that it was not just the volume of words exchanged over networks that could be analysed but also the variety of user generated content such as images and videos (Mayer-Schönberger and Cukier, 2013). The increasing use of social media among a wide scope of peoples across the world, enabled by the growing ubiquity of affordable smartphones (Miller et al., 2016) meant that images, videos and the responses, comments and shares were becoming richly varied, and that the pace of transactions was accessible to analysis. That accelerated pace is the third key big data characteristic; velocity (Mayer-Schönberger and Cukier, 2013). This characteristic, where the pace of data generation and data analysis is emphasised, highlights how the impact of big data is more than a generic description of many records, and points to how embedded decision making using machine learning driven by real time data is changing the power relationships at the heart of capitalism. The next section will look at the rise of big data as a form of capitalist extractive venture, before moving to some of the critical responses to big data. |
| Keywords | Critical Management Scholarship |
| Big Data | |
| Algorithm | |
| AI | |
| Artificial Intelligence | |
| Surveillance Capitalism | |
| Critical Management Studies | |
| Book title | Elgar Encyclopedia of Critical Management Studies |
| Year | 2025 |
| Publisher | Edgar Elgar Publishing |
| Publication dates | |
| Published | Apr 2025 |
| Place of publication | Chichester |
| ISBN | 9781800377714 |
| 9781800377721 | |
| Web address (URL) | https://www.e-elgar.com/shop/gbp/elgar-encyclopedia-of-critical-management-studies-9781800377714.html |