Big Data Analytics (BDA)
The Big Data Analytics course is an Advanced Development Module (MA) eligible by students pursuing a Master of Science in Engineering. It corresponds to 3 ECTS credits.
Professors | Nastaran Fatemi and Marcel Graf | ||||||||||||||||||
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Assistant | Fatemeh Borran | ||||||||||||||||||
Master Research Unit | TIC / HEIG-VD | ||||||||||||||||||
Eligible in these specialisations | TIC / Software Engineering
TIC / Distributed information systems and multimedia |
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Time constraints | None | ||||||||||||||||||
Capacity | Min. 5, max. 40 | ||||||||||||||||||
Location | Yverdon-les-Bains | ||||||||||||||||||
Summary |
This class will be taught by Prof. Nastaran Fatemi and Prof. Marcel Graf. Since many years structured data, typically stored in relational databases, has been analyzed with data warehousing technologies for the benefit of marketing and financial decision taking. The rapid development of social networks and the ubiquity of computing in everyday life have lead to the creation of large volumes of data (Big Data), mostly unstructured: web logs, videos, audio files, photos, emails, tweets, etc. At the same time, following Moore's law, CPU power has increased and storage space has become cheaper. Today we have the possibility to store reliably huge amounts of data for an almost negligeable cost. This data can be efficiently analyzed to extract insights useful for business and social life. This course presents techniques to manipulate, store and analyze large volumes of data (Hadoop, tools for accessing non-structured data Pig and Hive, NoSQL databases and data mining techniques as well as their implementation for Big Data). |
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Content |
Subjects treated in this course and their allocated time:
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Prerequisites | None | ||||||||||||||||||
Evaluation | Written exam | ||||||||||||||||||
Teaching methods |
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