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Big Data Management and Analytics im SS 2017


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Content

In almost all areas of business, industry, science, and everybody's life, the amount of available data that contains value and knowledge is immense and fast growing. However, turning data into information, information into knowledge, and knowledge into value is challenging. To extract the knowledge, the data needs to be stored, managed, and analyzed. Thereby, we not only have to cope with increasing amount of data, but also with increasing velocity, i.e., data streamed in high rates, with heterogeneous data sources and also more and more have to take data quality and reliability of data and information into account. These properties referring to the four V's (Volume, Velocity, Variety, and Veracity) are the key properties of "Big Data". Big Data grows faster than our ability to process the data, so we need new architectures, algorithms and approaches for managing, processing, and analyzing Big Data that goes beyond traditional concepts for knowledge discovery and data mining. This course introduces Big Data, challenges associated with Big Data, and basic concepts for Big Data Management and Big Data Analytics which are important components in the new and popular field Data Science.


Organisation

  • Umfang: 3+2 hours weekly (equals 6 ECTS)
  • Required: Lecture "Database Systems I" or equivalent
  • Beneficial: Lecture "Knowledge Discovery in Databases I" or equivalent
  • Lecture: Prof. Dr. Matthias Schubert
  • Assisting:
  • Audience: This course is only open for participants of the Elite-Studiengang "Data Science"

Time and Locations

Component When Where Starts at
Lecture Thu, 9.00 - 13.00 Room 157 (Oettingenstr. 67) 27.04.2017
Tutorial Mo, 16.00 - 18.00 Room 118 (Amalienstr. 73A) 08.05.2017

Schedule

(Note: This schedule is tentative. As new course, chapters and dates could be updated on short notice)

Lecture Tutorial
Date Topic Date Topic

Vorhergehende Semester

WS 16/17, WS 15/16

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