Big data, bigger dilemmas: A critical review

By Hamid R. Ekbia, M. Mattioli, Inna Kouper, G. Arave, Ali Ghazinejad, T. Bowman, V. R. Suri, Andrew Tsou, Scott B. Weingart, Cassidy R. Sugimoto. 2015

294 citations recorded by the source corpus.

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain‐specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention—autonomy, opacity, generativity, disparity, and futurity—leading to questions and ideas for moving beyond dilemmas.

Subfields: Information Systems and Management, Management Information Systems, Management Science and Operations Research

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Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Ekbia et al. (2015) present a high-level survey of dilemmas involving any type of Big Data—without considering a prototypical data pipeline; including epistemological, methodological, aesthetic, technological, legal/ethical, and political issues.”
New games, new rules: big data and the changing context of strategy (2015, background): “In a recent paper, Ekbia et al. (2014) nicely capture the way we should look at the broader picture of issues and questions related to big data.”
The Pushshift Reddit Dataset (2020, background): “2019), a lack of concern for data sharing or reproducibility (Borgman 2012; Weller and Kinder-Kurlanda 2016), and failures to validate constructs or generalize to off-platform behavior (Ekbia et al. 2015; Howison, Wiggins, and Crowston 2011; Japec et al. 2015).”
How to improve firm performance using big data analytics capability and business strategy alignment (2016, background): “According to Ekbia et al. (2015), “big data is dark data”; thus, it needs to be investigated in a meaningful balanced manner by applying the right talent, technology, and strategy.”
Debating big data: A literature review on realizing value from big data (2017, background): “…et al., 2014; Krishnamoorthi and Mathew, 2015), mediated by several factors such as data-driven and analytical culture (Cao and Duan, 2014; Duan and Cao, 2015; Kulkarni and Robles-Flores, 2013); leadership commitment and user involvement (Kulkarni and Robles-Flores, 2013); the decision environment…”
The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity (2019, background): “However, we suggest that while algorithm-based HR decision-making aggravates some of the already known quandaries (Ekbia et al. 2015), it also creates novel tensions, such as increased information asymmetries between management and employees, thereby reducing employees’ sense of autonomy and,…”