Moses - BDASEM - Big Data Analytics Seminar

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum SS 2014 - SS 2015. Die Version für das aktuelle Semester (SoSe 2024) finden Sie hier: Modulbeschreibung des SoSe 2024

Module / Version:
#40353 / #1

Validity:
SS 2014 - SS 2015

Default display language:
English

Module title:
BDASEM - Big Data Analytics Seminar

Credits:
3

Responsible person:
Markl, Volker

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Softwaretechnik und Theoretische Informatik

Area of expertise:
34351500 FG Datenbanksysteme und Informationsmanagement (DIMA)

Prüfungsausschuss:
No information

Kontakt

Office:
EN 7

Contact person:
Soto, Juan

E-mail address:
sekr@dima.tu-berlin.de

Website:

https://www.tu.berlin/dima

Learning Outcomes

Participants of this seminar will acquire knowledge about recent research results and trends in the analysis of web-scale data. Through the work in this seminar, students will learn the comprehensive preparation and presentation of a research topic in this field. In order to achieve this, students will get to read and categorise a scientific paper, conduct background literature research and present as well as discuss their findings. After the course, students will be able to critically read and evaluate scientific publications, and to conduct background research. They will be capable of preparing for and giving oral presentations on research topics for an expert audience, of analyzing the state of the art of a research topic, and of summarizing it in a scientific paper. They should also understand techniques used in the scientific community like peer reviews, conference presentations, and defenses of the findings after their presentation, as well as they should understand methods for large-scale data analytics. The course is principally designed to impart: Technical skills: 50x Methodological skills: 20x System skills: 10x Social skills: 20x

Content

Both the sciences and industry are currently undergoing a profound transformation: largescale, diverse data sets - derived from sensors, the web, or via crowd sourcing - present a huge opportunity for data-driven decision making. This data poses new challenges in a variety of dimensions: in its unprecedented volume, in the speed at which it is generated (its velocity) and in the variety of data sources that need to be integrated. A whole new breed of systems and paradigms is currently developed to be able to cope with that these challenges. The field of Big Data Analytics deals with the technological means of gaining insights from huge amounts of data. In this seminar, students will review the current state of the art in this field. At the beginning of the semester you will receive a set of primary literature, which consists of a basic item for every participant. Then you will learn about presentation techniques and guidelines on how to read scientific papers. This is be extended by learning how to write texts specially in the context of the English language. Then you should use secondary sources to research your topic assigned to you in the seminar, which should go beyond the supplied primary literature. Next to conventional sources like the internet you are required to use research journals and articles published at information management conferences such as WWW, VLDB, or SIGMOD.

Module Components

Pflichtteil:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
BDASEM - Big Data Analytics Seminar	SEM	0434 L 477	WiSe	No information	2

Workload and Credit Points

BDASEM - Big Data Analytics Seminar (SEM):

Workload description	Multiplier	Hours	Total
Präsenzzeit	15.0	2.0h	30.0h
Vor-/Nachbereitung	15.0	4.0h	60.0h
			90.0h(~3 LP)

The Workload of the module sums up to 90.0 Hours. Therefore the module contains 3 Credits.

Description of Teaching and Learning Methods

About four weeks after receiving the primary literature you will have to give a short presentation which should last about 10 minutes. The presented topic will then be discussed for about 10 minutes by the seminar group. This is done so that the other seminar participants can give you constructive feedback about the content of your talk. At the end of the semester you will have to give another talk which should be about 30 minutes long. In addition to the talk you will also have to hand in a 10 page report describing and evaluating the topic.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

This course is aimed at master students with a focus on database systems and information management and should be chosen after the 2nd semester. To be able to participate you must have successfully completed IDB and AIM. In the ideal case this seminar should be taken by students who are directly in front of their master thesis or have already completed it and are interested in a doctorate in information management.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

No information

Language

English

Test elements

Name	Points/Weight	Categorie	Duration/Extent
presentation	50	No information	No information
written seminar report	50	No information	No information

Grading scale

No information

Test description (Module completion)

No information

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Wintersemester.

Maximum Number of Participants

The maximum capacity of students is 16.

Registration Procedures

Students are required to register via the DIMA course registration tool before the start of the first lecture (http://www.dima.tu-berlin.de/). Within the first six weeks after commencement of the lecture, students will have to register for the course at QISPOS (university examination protocol tool) and ISIS (course organization tool) in addition to the registration at the DIMA course registration tool.

Recommended literature
Will be released at the beginning of the seminar.

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

This module is used in the following Degree Programs (new System):

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

Students of other degrees can participate in this module without capacity testing.

Wahlpflichtmodul im Masterstudiengang Wirtschaftingenieurswesen (Studiengang IuK).

Miscellaneous

No information

BDASEM - Big Data Analytics Seminar

Zugehörigkeit

Kontakt

Learning Outcomes

Content

Module Components

Pflichtteil:

Workload and Credit Points

BDASEM - Big Data Analytics Seminar (SEM):

Description of Teaching and Learning Methods

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Mandatory requirements for the module test application:

Module completion

Grading

Type of exam

Type of portfolio examination

Language

Test elements

Grading scale

Test description (Module completion)

Duration of the Module

Maximum Number of Participants

Registration Procedures

Recommended reading, Lecture notes

Lecture notes

Electronical lecture notes

Literature

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Miscellaneous