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This entry is from Summer semester 2021 and might be obsolete. You can find a current equivalent here.

CS 671 — Data Integration
(dt. Datenintegration)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Examination type: Oral or written examination
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Data Science.
Duration,
frequency		 One semester,
Zweijährlich im Sommersemester
Person in charge of the module's outline Prof. Dr. Bernhard Seeger

Contents

  • Semantic data models
  • Extraction of data and metadata
  • data preprocessing
  • Techniques of schema transformation
  • Fast loading of data
  • Architecture for data warehouses
  • Online analysis in data warehouses
  • Continuous loading and data streams (message queuing)
  • Coupling techniques for database systems
  • Data exchange on the Web

Qualification Goals

  • Knowledge of semantic data models,
  • Learn techniques for linking databases,
  • Acquisition of knowledge of techniques in schematic transformation,
  • Principles of data warehousing,
  • Analysis techniques for large databases,
  • Principles of message queuing,
  • Practice of scientific working methods (recognition, formulation, solving problems, training of abstraction skills),
  • Training of oral communication skills in the exercises by practicing free speech in front of an audience and during discussion.

Prerequisites

None. The competences taught in the following modules are recommended: either Algorithms and Data Structures or Practical Informatics II: Data Structures and Algorithms for Pre-Service-Teachers, Database Systems.


Applicability

Module imported from M.Sc. Data Science.

It can be attended at FB12 in study program(s)

  • B.Sc. Data Science
  • B.Sc. Computer Science
  • B.Sc. Business Informatics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Informatics
  • M.Sc. Business Mathematics
  • LAaG Computer Science

When studying M.Sc. Computer Science, this module can be attended in the study area Specialization Modules in Computer Science.

The module is assigned to Practical Computer Science. Further information on eligibility can be found in the description of the study area.


Recommended Reading

  • Han,Kamber: Data Mining: Concepts and Techniques, Morgan Kaufmann
  • Lehner: Datenbanktechnologie für Data-Warehouse-Systeme, Dpunkt
  • Conrad: Föderierte Datenbanksysteme - Konzepte der Datenintegration. Springer-Verlag
  • Naumann: Quality-Driven Query Answering for Integrated Information Systems, Springer-Verlag



Please note:

This page describes a module according to the latest valid module guide in Summer semester 2021. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.