Lehr- und Forschungseinheit für Datenbanksysteme
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Big Data Management and Analytics (WS 2019/20)

News

  • [31.10.19] The exam will take place on Friday 21.02.2020 12-14 in the lecture halls B 201 and M 218. The registration via Uni2Work will be opened soon.
  • [24.10.19] The tutorial today (Thursday 24.10) at 16-18 will take place (only today) in Professor-Huber-Platz 02, W 101.
  • [24.10.19] Update: The locations for the tutorials on Thursday changed for the 31.10 onwards . Please look below for updated building and room information.
  • [11.10.19] Please register for the course via uni2work. Slides for the lecture, exercise sheets and other material will be published exclusively there.

Organisation

  • Umfang: 3+2 hours weekly (equals 6 ECTS)
  • Lecture: Prof. Dr. Matthias Schubert
  • Assistants: Daniyal Kazempour, Anna Beer 
  • Required: Lecture "Database Systems I" or equivalent
  • Beneficial: Lecture "Knowledge Discovery in Databases I" or equivalent
  • Audience: The lecture is directed towards Bachelor students (5th term) and Master students in Mediainformatics, Bioinformatics, and Informatics

Time and Locations

All times are c.t. (cum tempore)

Component When Where Starts at
Lecture Tue, 13.00 - 16.00 h Room S 004 (Schellingstr. 3) 15.10.2019
Tutorial 1 Wed, 16.00 - 18.00 h Room D Z007 (HGB) 23.10.2019
Tutorial 2 Wed, 18.00 - 20.00 h Room D Z007 (HGB) 23.10.2019
Tutorial 3 Thu, 14.00 - 16.00 h Room C 112 (Theresienstr. 37/39/41) 24.10.2019
Tutorial 4 Thu, 16.00 - 18.00 h Room S 005 (Schellingstr. 3) 24.10.2019

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.

 

Course Schedule

LectureTutorial
DateTopicDateTopic
15.10.19 Lecture 1: Data Science: The Big Picture 16.10.19
17.10.19
-
22.10.19 Lecture 2: NoSQL Databases 23.10.19
24.10.19
29.10.19 Lecture 3: Batch Systems 30.10.19
31.10.19
5.11.19 Lecture 4: Apache Spark 06.11.19
07.11.19
12.11.19 Lecture 5: Stream Processing 13.11.19
14.11.19
19.11.19 Lecture 6: Apache Flink 20.11.19
21.11.19
26.11.19 Lecture 7: Stream Analytics 27.11.19
28.11.19
03.12.19 Lecture 7: Stream Analytics cont. 04.12.19
05.12.19
10.12.19 Lecture 8: High Dimensional Data 11.12.19
12.12.19
17.12.19 Lecture 8: High Dimensional Data cont. 18.12.19
19.12.19
24.12.19
-06.01.20
Happy Holidays !!!
07.01.20 Lecture 9: Community Detection 08.01.20
09.01.20
14.01.20 Lecture 10: Node Importance and Neighborhoods 15.01.20
16.01.20
21.01.20 Lecture 10: Python for Data Analytics - Best Practices 22.01.20
23.01.20
28.01.20 Lecture 11: The Flip Side of the Coin 29.01.20
30.01.20
04.02.20 Q&A 05.02.20
06.02.20