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Real World-Big Data Analytics in Healthcare.
Daniele Piovani1,2, Stefanos Bonovas1,2
1Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20090 Milan, Italy.
International Journal of Environmental Research and Public Health
|September 23, 2022
Summary
Big Data refers to massive, complex datasets that require advanced informatics and statistical methods. Analyzing this data reveals significant patterns and trends for various applications.
Area of Science:
- Computer Science
- Statistics
- Information Science
Background:
- Big Data involves extremely large, complex, multi-dimensional, unstructured, and heterogeneous datasets.
- These datasets are accumulating at an unprecedented and rapid rate.
- Traditional data processing methods are insufficient for managing and analyzing Big Data.
Discussion:
- Appropriate informatics and statistical methodologies are crucial for Big Data analysis.
- The analysis aims to reveal underlying patterns, trends, and associations within the data.
- Understanding these insights can drive informed decision-making and innovation.
Key Insights:
- Big Data analytics enables the discovery of hidden correlations and predictive insights.
- The effective utilization of Big Data can lead to advancements in scientific research and business intelligence.
- Challenges include data storage, processing power, and analytical expertise.
Outlook:
- Future research will focus on developing more efficient algorithms and scalable infrastructure for Big Data.
- The integration of artificial intelligence and machine learning will further enhance Big Data analysis capabilities.
- Ethical considerations and data privacy will remain critical aspects of Big Data research and application.
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