Big Data Management and Analytics im WS 15/16
Die Klausur-Einsichtnahme findet am Freitag, den 19. Februar 2016 von 13:00 bis 15:00 Uhr im Raum 156 in der Oettingenstraße statt.
The exam will be held on Friday February 5th, 2016, between 14.00 and 16.00 in hall A140, main building. Please Register via Uniworx. Students who have not registered beforehand may not be admitted to the exam!
Die Klausur findet statt am Freitag 5. Februar 2016 von 14:00 bis 16:00 Uhr im Raum A140, Hauptgebäude. Bitte registrieren Sie sich für die Teilnahme unter Uniworx. Teilnahme kann nur bei vorheriger Registrierung garantiert werden!
News
- Die Klausur-Einsichtnahme findet am Freitag, den 19. Februar 2016 von 13:00 bis 15:00 Uhr im Raum 156 in der Oettingenstraße statt.
- Am 1.2. findet keine Übung mehr statt.
- Die Templates zur Übung 3 wurden aktualisiert!
- Die Vorlesung am 05.11.2015 entfällt
- Der Übungsbetrieb beginnt erst am 02.11.2015!!!
- Registration for this lecture is now open via Uniworx
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
- Required: Lecture "Database Systems I" or equivalent
- Beneficial: Lecture "Knowledge Discovery in Databases I" or equivalent
- Lecture: Prof. Dr. Matthias Renz
- Assisting: Felix Borutta, Evgeniy Faermann, Christian Frey, Klaus Arthur Schmid
- Tutors:
Time and Locations
| Component | When | Where | Starts at |
|---|---|---|---|
| Lecture | Thu, 8.45 - 11.00 | Room B U101 (Oettingenstr. 67) | 15.10.2015 |
| Tutorial 1 | Mon, 14.00 - 16.00 | Room D Z003 (Main Building, Geschwister-Scholl-Platz) | 26.10.2015 |
| Tutorial 2 | Mon, 16.00 - 18.00 | Room D Z003 (Main Building, Geschwister-Scholl-Platz) | 26.10.2015 |
Schedule
(Note: This schedule is tentative. As new course, chapters and dates could be updated on short notice)
| Lecture | Tutorial | ||
|---|---|---|---|
| Date | Topic | Date | Topic |
| 15.10.15 | Chapter 0: Intro&Overview Chapter 1: Introduction to Big Data — the four V's | --- | |
| 22.10.15 | V1: Volume — Chapter 2 Part 1: NoSQL Databases | --- | |
| 29.10.15 | V1: Volume — Chapter 2 Part 2: NoSQL Databases | 02.11.15 | Introduction to Python Slides Code |
| 05.11.15 | entfällt | 09.11.15 | Examples for NoSQL Slides |
| 12.11.15 | V1: Volume — Chapter 3 - Part 1: Hadoop, MapReduce, HDFS | 16.11.15 | MR Examples and Templates (updated) Slides Templates |
| 19.11.15 | V1: Volume — Chapter 3 - Part 2: Hadoop, MapReduce, HDFS | 23.11.15 | MR Examples II and Code solutions Slides Code |
| 26.11.15 | V1: Volume — Spark | 30.11.15 | FPGrowth Algorithmus in Spark Slides (update) Code |
| 03.12.15 | V2: Velocity — Stream Processing | 07.12.15 | Streaming I (korrigierte Version) |
| 10.12.15 | V2: Velocity — Stream Applications and Algorithms | 14.12.15 | Exercise sheet Slides (update) |
| 17.12.15 | V3: Variety — Text processing and high dimensional data (new version) | 21.12.15 | Exercise sheet Slides |
| Winter Break | |||
| 07.01.16 | V3: Variety — Text processing and high dimensional data (cont.) | 11.01.16 | Exercise sheet Slides |
| 14.01.16 | V3: Variety — Graph Data: Part 1, Link Analysis and PageRank | 18.01.16 | Exercise sheet Slides |
| 21.01.16 | V3: Variety — Graph Data: Part 2, Community Detection | 25.01.16 | Exercise sheet |
| 28.01.16 | V4: Veracity — Uncertain Data: Managing and Querying Uncertain Data | 01.02.16 | No tutorial |
| 05.02.16 | Exam | --- | |
