An introduction to data storage and manipulation at both desktop and cloud scales. Introduces core database concepts and provides a practical introduction to both SQL and NoSQL systems. Also introduces parallel and distributed computing concepts including distributed storage and large scale parallel data processing using MapReduce. Design and implementation of new data visualizations to aid analysis, with emphasis on the practical and ethical implications of design and analysis decisions.
This course may not be repeated for credit.
Prerequisite(s)
- Data Science 601 and admission to the Graduate Certificate in Fundamental Data Science and Analytics or the Graduate Diploma in Data Science and Analytics.
Sections
This course will be offered next in
Fall 2020.