GoalsThe rise of user-web interaction and networking, coupled with technological advances in processing power and storage capability, has led to a growing demand for effective and sophisticated techniques for discovering and managing knowledge. Businesses need to transform large quantities of raw data into knowledge, and they rely on modern database and knowledge management systems to make informed and often business-critical decisions. Similarly, scientists have to process massive amounts of data to gain new insights and advance reseach.
The master program will equip students with the fundamental knowledge, technical skills and concrete applied methodologies for exploiting and making sense of large real-world data sets, which are typically very large and may consist of multiple heterogeneous databases and knowledge bases. In particular, students will acquire experience in using and developing data-supported smart services and tools for data-driven decision making and will learn how to master technical and scientific challenges in processing large data and knowledge. The program will prepare students for careers as information management professionals or data-savvy IT generalists, or for research in areas related to discovery and management of very large data and knowledge.
Professional careersThe Data&Knowledge track will prepare students for careers as information management professionals or data-savvy IT generalists, or for research in areas related to discovery and management of very large data and knowledge. Potential carreers include : IT executives in businesses, careers in research and development in universities and private research, IT careers in large companies and start-ups. Targeted job profiles are software engineer, data scientists, software and system architects, quality engineers, project managers, engineers, or researcher.
Research CareersThe combination of big data and semantics in all of its forms is an active field of research. Students will be prepared for research in Web technologies, the Social Web, Data Analytics, Big Data Management, Knowledge Base Management, Information Extraction, Information Retrieval, Databases, Data Warehousing, Knowledge Representation, and Distributed Data Management.
Students who wish to pursue a PhD afterwards are more than encouraged to do that. The Paris Saclay University and the associated research labs (INRIA, CNRS, etc.) offer an optimal environment for a PhD, and our program is an optimal preparation for this path.