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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


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

Slides (update)

28.01.16 V4: Veracity — Uncertain Data: Managing and Querying Uncertain Data 01.02.16 No tutorial
05.02.16 Exam ---

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