The bright side of big data: the role of data literacy in mitigating negative effects on task performance

Abstract While the proliferation of Big Data (BD) increasingly pressures task execution in the workplace, the underlying socio-cognitive pathways linking data demands to worker performance remain fragmented. The objective of this research is to analyze the effect of BD on Task Performance (TP), investigating the mediating roles of Cognitive Overload (CO), Avoidance Behavior (AB), and Data Literacy (DL), and the moderating role of DL in mitigating the negative effects of AB on TP. Grounded in the Situation-Organism-Behavior-Consequence (SOBC) and Job Demands-Resources (JD-R) models, this study surveyed 372 data workers in Brazil, analyzing empirical data using Partial Least Squares Structural Equation Modeling (PLS-SEM). We discovered a dual-pathway mechanism influencing TP. The deterioration process operates as a negative loop where CO and AB deplete professional energy, whereas the motivational path triggers DL mobilization to enhance performance. Mediation indicates that DL and AB are significant intermediaries, while moderation indicates that DL buffers AB’s detrimental impact on TP. Specific triggers include Veracity as a cognitive anchor and Velocity as an engagement catalyst. Theoretically, this research highlights how data characteristics shape cognitive states and positions DL as a key resource for sociocognitive resilience. For practice, identifies DL as the strategic priority for organizational intervention to optimize performance. Socially, the study promotes well-being by identifying mechanisms that translate informational complexity into professional effectiveness. The study’s originality lies in explaining the critical tension surrounding the BD, showing that while its demands can lead to exhaustion (dark side), they also mobilize resources that catalyze resilience (bright side).