Purpose: With the digitisation of healthcare, more data than ever is being generated. Big data refers to “extremely large and complex datasets that cannot be easily managed or analysed with traditional data processing tools, particularly spreadsheets”. Methods: This is a scoping review of the role, advantages and limitations of the use of administrative databases in healthcare. Results: Administrative datasets in healthcare are high volume data collected for non-clinical purposes but includes clinical information such as comorbidities, procedures, re-admissions, and longitudinal survival outcomes at a population level. Surgery is a unique specialty where disease acuity, high costs, ethical implications and decreased feasibility of RCTs result in more research constraints compared to other specialties. Big administrative data is advantageous in its strongly powered in sample size and longitudinal data. The storage, analysis and interpretation of sensitive demographic and health care data is challenging due to its enormous magnitudes, data custodianship, privacy issues and difficulties in clinical integration. As a ginormous observational study, population based administrative datasets have the same limitations of confounding, measurement error and selection bias as retrospective cohort studies. Observational studies are more prone to exaggerated effect size and statistical significance. Conclusion: Administrative datasets are unique forms of big data with capabilities in hypothesis generation, and identification of risk factors and disease associations. The future of big data in healthcare will be in the prediction of patient outcomes at an individual level and personalised clinical decision-making.