Big Data and Scripting (SS 2014)
+++ Announcements +++
|Lecture (U. Nagel)
||Mon 13:30–15:00 (M628)
Thu 10:00–11:30 (E402)
|Tutorial (M. Ortmann)||Fri 10:00–11:30 (F420) (Group A)
Fri 13:30–15:00 (F420) (Group B)
|written exams (exam time 90 minutes)||July 30., 2 p.m (14 Uhr)||A704|
|Oktober 14., 1 p.m. (13 Uhr)||C336|
The term ``big data'' is often used to describe vast collections of semi-structured data in the range of tera- or even petabytes. Companies like Google and Amazon illustrate that mining and analyzing such collections yields the potential for completely new applications.
The lecture provides an overview of motivations to analyze big data and introduces techniques needed in the process. This includes introductions to scripting languages, NOSQL databases and Map/Reduce systems which are accompanied by practical exercises.
Course material will be made available on this page over the course of the lecture, mostly in form of the slides used in the lecture. In addition there will be regular practical assignments to be solved in groups which will be also topic of the tutorials.
The assignments are returned and discussed during the tutorials. 50 percent of the total score of the assignments and regular attendance at the tutorials are necessary to be admitted to the final exam.
You are permitted and encouraged to work in groups of two. For your submission please follow the instructions given in assignment00.
|0||April 28.||May 2.||a00.pdf||data.tar.gz|
|1||April 28.||May 9.||a01.pdf||tables.txt|
|2||May 5.||May 16.||a02.pdf|
|3||May 12.||May 23.||a03.pdf||random.awk|
|4||May 19.||May 30.||a04.pdf||2013_02_08_01.zip|
|5||May 26.||June 6.||a05.pdf||multigauss.py, example.py|
|6||June 2.||June 13.||a06.pdf|
|7||June 10.||June 20.||a07.pdf||newsgroups.zip|
|8||June 16.||June 27.||a08.pdf|
|9||June 23.||July 11.||a09.pdf|
|10||July 7.||July 18.||a10.pdf|
Textbooks/ other material
|© 2014 Universität Konstanz · last update 19.07.2016|