The students must acquire the necessary knowledge to model, import, tidy, transform, query, visualize, and analyze data as well as to communicate the results of the analysis. We take into consideration relational data as well as semistructured and unstructured data. The students must learn languages and tools such as PostgreSQL, BaseX, R, RStudio, Processing, and the R Markdown language for the communication of the results of the analysis.
Data Management
Learning Goals
Program in pills
Fundamentals of database systems: design, develop, populate, and manipulate a relational database. Advanced database models, languages, and systems: advanced query processing techniques for relational databases. Basic elements of distributed and parallel database management systems. Data analysis and big data: main techniques and tools for data analysis and big data management. A number of key topics will be addressed, ranging from the MapReduce paradigm to time series and text analytics.
Area
Computer Science and Intensive Computing
Curriculum Foundations
TAF Type
Curriculum Industry
TAF Type
Curriculum Health
TAF Type
Curriculum Economy
TAF Type
SSD
ECTS
Semester
Lecturers
Adriano Peron