Miss Cris Guerrero Romero
Email: email@example.comRoom Number: Peter Landin, CS 335
Semi-structured Data and Advanced Data Modelling (Postgraduate/Undergraduate)
In this module, student will learn to process XML (with XSLT and Java), to model data with XML (XML native, RDF), and to query XML data (XQuery). The module teaches many concepts of data modelling and knowledge representation that are beyond the syntactic issues of XML or RDF. The knowledge students acquire in the course is fundamental to the many data design and data analytics tasks occurring in todays IT and business landscapes. The second part of the module is dedicated to advanced DB concepts including active databases, mobile databases, spatial and temporal databases, triggers, performance tuning, distributed databases, indexing and query optimisation. The third part of the module covers the modern, agile world of data processing: NoSQL. It is about the processing of semi-structured data, transforming data streams into formats (triplets, JSON) to be processed by new DB systems (e.g. MongoDB, CouchDB). Overall, students will learn in this module to solve data and information management tasks as they typically occur in today's IT landscape.