Business Intelligence & Data Management
Exam number: 3091
Semester: from 4th semester (Schwerpunktbildung)
Duration of the module: One semester
Form of the module (i.e. obligatory, elective etc.): Elective
Frequency of module offer: Each summer semester
Prerequisites: Fundamentals of Business Informatics. Grundlagenausbildung should be completed.
Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.
Person responsible for module: Prof. Dr. Achim Koberstein (until summer semester 2014: Prof. Dr. Karl Kurbel)
Name of the professor: Prof. Dr. Achim Koberstein (until summer semester 2014: Prof. Dr. Karl Kurbel)
Language of teaching: English
ECTS-Credits (based on the workload): 6
Workload and its composition (self-study, contact time):
Contact time (lecture, tutorials, seminar etc.) 45 h; self-study: 135 h
Contact hours (per week in semester): 4
Methods and duration of examination:
Successful written exam (120 min) and participation in all classes
Emphasis of the grade for the final grade: Please check regulations of the study programme
Aim of the module (expected learning outcomes and competencies to be acquired):
After participation in the course, students are able to technically communicate with BI specialists, to understand and apply dedicated BI solutions, to create prototypes of databases, and to design reports and BI processes. Good command of Excel and VBA are practical skills the students gained in the course.
Contents of the module:
Business Intelligence is an approach to extract valuable information for managerial decision making, e.g. for marketing decisions, from various sources. Microsoft Excel provides useful features and capabilities for Business Intelligence and is often used as a frontend for more advanced solutions such as Microsoft Analysis Services, Hyperion, MicroStrategy and SAP Business Objects.
Databases and data warehouses are the basis for Business Intelligence. Data from operational databases are extracted, transformed and loaded and into a data ware-house (ETL).
Data management is about modeling and organizing a company's oeprational data in a meaningful way. Common approaches to modeling are the entity-relationship model (ERM) and the relational data model, leading finally to enterprise-wide databases implemented with the help of a relational database management system (RDBMS). Data warehouses use different data models, such as the star model and snowflake model and multidimensional cubes for online analytical processing (OLAP).
We will deal with these models briefly and see how data are modeled and organized for Business Intelligence.
1 MS Excel for Business Intelligence
1.1 Important Excel functionality
1.2 Pivot tables
1.3 Excel features for OLAP
2 Server-based solutions for Business Intelligence
2.1 Online analytical processing (OLAP), data mining and more
2.2 Microsoft server solutions and other solutions on the market
3 Data management
3.1 Data modeling
3.2 Database management systems
3.3 Data warehouses and data marts
4.1 Applications for business
4.2 More BI areas
Teaching and learning methods:
Lectures, exercises, hands-on work, self-studies
Literature (compulsory reading, recommended literature):
Registration in Moodle Viadrina required.