Data Science Primer

Thomas Brennan

LCP, MIT

Analyzing Biomedical Big Data (BBD) is computationally expensive due to high dimensionality and large data volume. Performance and scalability issues of traditional databases often limit the usage of more sophisticated and complex data queries and analytic models. Moreover, in the conventional setting, data management and analytic are carried out in separate software platforms. Exporting and importing large amount of data across platforms requires a significant amount of computational and I/O resources, as well as potentially putting sensitive data at risk.

Through the following video we will learn the advantages of an in-memory databases over the traditional ones through hands-on exercises with the Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) database, a large clinical database with over 60,000 ICU stays.