Stud.IP Uni Oldenburg
University of Oldenburg
13.10.2019 22:08:42
inf604 - Business Intelligence I (Complete module description)
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Module label Business Intelligence I
Module code inf604
Credit points 6.0 KP
Workload 180 h
Faculty/Institute Department of Computing Science
Used in course of study
  • Master of Education Programme (Vocational and Business Education) Computing Science (Master of Education) >
  • Master's Programme Business Informatics (Master) >
  • Master's Programme Computing Science (Master) >
Contact person
Module responsibility
Authorized examiners
Entry requirements
Skills to be acquired in this module
Objective of the module/skills:
Current module provides basics of business intelligence with focus on enterprises and strong emphasis on data warehousing technologies. Students of the course are provided with knowledge, which reflects current research and development in a data analytic domain.

Professional competence
The students:
  • name and recognize the role of business intelligence as past of daily business process
  • being able to analyse advantages and disadvantages of different approaches and methods of the data analytics and being able to apply them in simple case studies
  • obtain theoretical knowledge about data collection and modelling processes, including most applicable approaches and best practices


Methodological competence
The students:
  • being able to execute typical tasks of business intelligence, and also being able to deepen knowledge on different approaches and methods
  • gain a hans on experience and being able to understand advantages and disadvantages of different methods and being able to use obtained knowledge in most efficient ways


Social competence
The students:
  • build solutions based on case studies given to the group, for example solving the issue of a factless fact table
  • discuss solutions on a technical level
  • present obtained case studies solutions as part of the exercises


Self-competence
The students:
  • critically review provided data and information
Module contents
Data warehouse technology together with business intelligence are increasingly being used by business in order to get better decision support and enrich ongoing rocesses with data-rich decisions. Data warehouse technology enables an integration of data from heterogeneous sources, whether business intelligence builds data rocessing on top of it. For instance, business intelligence allows to build reporting on very large volumes of data (including historical) coming primary from data warehouse.

As past of the current module following contents are taught:
  • Definition and scope of business intelligence.
  • Procedures and objectives of data warehousing.
  • Process of extracting, transforming and loading (ETL) of data.
  • Phases of data modelling, data capturing and reporting in conjunction with a plausible case studies/scenarios.
  • Prospects for further and evolving topics for business intelligence (e.g. Adaptive Business Intelligence, In-MemoryComputing. etc.)
  • Introduction to Data Mining.
  • Case studies based practical exercises and assessments in order to impart practical knowledge.
Reader's advisory
  • Adamson (2010): The complete reference star schema.
  • Jensen, Pedersen, Thomsen (2010): Multidimensional Databases and Data Warehousing (Synthesis Lectures on Data Management).
  • Loshin (2012): Business Intelligence – The Savvy Manager’s Guide.
  • Marx Gómez, Rautenstrauch, Cissek (2008): Einführung in die Business Intelligence mit SAP NetWeaver 7.0.
  • Müller, Lenz (2013): Business Intelligence.
  • Sabherwal, Becerra-Fernandez (2010): Business Intelligence: Practices, Technologies, and Management
Links
Languages of instruction German, English
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel AS (Akzentsetzung / Accentuation)
Modulart Wahlpflicht / Elective
Lern-/Lehrform / Type of program V +Ü
Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload attendance
Lecture 2.00 WiSe 28 h
Exercises 2.00 WiSe 28 h
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
At the end of the lecture period
Written exam max. 120 minutes