Big data
Digital Health and AI
Definition. Big data refers to datasets whose volume, velocity and variety exceed the capacity of conventional data management and analysis tools.
Explanation
The term is usually defined by the three Vs of volume, velocity and variety, with veracity and value often added. In health care, sources include electronic records, claims, registries, imaging, genomics, wearables and social media.
Raghupathi and Raghupathi (2014) describe the promise of big data analytics for population health, prediction and operational management. The main difficulties are data quality, linkage, governance and privacy, and the risk that large but biased datasets produce confident but wrong conclusions.
Related concepts
Machine learning Electronic health record (EHR) Interoperability Learning health system
Read on The Health Topics
- Industry 4.0 and Health: Revolutionizing Healthcare
- AI’s Role in Modern Drug Regulation
- Digital Healthcare: Progress and Applications
- Digital Twins in Healthcare:The Technology That Wants to Clone You — Virtually
- Machine Learning for Public Health Policy Evaluation
- The Most Popular Research Methods and Analysis Techniques in Management and Organisation Research
References
Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems, 2, 3.
Cite this entry: Kurutkan, M. N. (2026). Big data. In The Health Topics glossary. https://healthtopic.org/glossary/big-data/
Articles that discuss this concept
23 articles on The Health Topics use this concept; the 12 that use it most are listed. The list updates as new articles are published.
- Industry 4.0 and Health: Revolutionizing Healthcare 17
- Digital Healthcare: Progress and Applications 6
- AI’s Role in Modern Drug Regulation 6
- Machine Learning for Public Health Policy Evaluation 3
- Digital Twins in Healthcare:The Technology That Wants to Clone You — Virtually 3
- Digitalization in Medicine: A Bibliometric Insight 2
- Fog Computing for Healthcare 4.0: Opportunities and Challenges 2
- Digital Twin in Industry: State-of-the-Art 2
- The Intersection of Artificial Intelligence and Health Technology Assessment 2
- Quality 4.0 awareness, challenges, readiness and core skills 2
- NCA-ESSE: Enhancing Necessary Condition Analysis in Data Science 2
- The Sense and Nonsense of Effect Size: What Does Funder and Ozer’s (2019) Call Mean for Health Research? 2