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Data Design & Modeling


Data design and modeling provides the foundation for representing, storing and managing structured, semi-structured and unstructured data. Data can be persistent or volatile, processed in batches or in continuous streams. Students will learn: - how to select appropriate data management solutions to deal with scalability, availability, consistency, performance and expressiveness requirements - the big data dimensions: volume, velocity, variety and veracity - the CRUD primitives (create, read, update, delete) implemented at scale - the ACID/BASE transactional properties of existing SQL/NOSQL data management technologies - how to choose suitable sharding and replication strategies - the data analysis pipeline: Acquisition, Integration, Exploration, Mining, Analytics, Interpretation and Visualization - data quality, provenance, wrangling and cleansing to ensure data is worthy of trust Students will experiment with big data technologies with hands-on use cases and practical use of cloud big data platforms.



Brambilla M.

Course director

Leppänen S.


Additional information

Academic year
Master of Science in Informatics, Elective course, Lecture, 1st and 2nd year

Master of Science in Software & Data Engineering, Core course, Lecture, 1st year