syllabus
1. Information regarding the programme
1.1 Higher education institution 	Babeş Bolyai University	
1.2 Faculty	Faculty of Mathematics and Computer Science	
1.3 Department	Department of Computer Science	
1.4 Field of study	Computer Science	
1.5 Study cycle	Bachelor	
1.6 Study programme / Qualification 	Computer Science	

2. Information regarding the discipline 
2.1 Name of the discipline	Business Intelligence	
2.2 Course coordinator 	Lect. Dr. Anca Andreica	
2.3 Seminar coordinator	Lect. Dr. Anca Andreica	
2.4. Year of study	3	2.5 Semester	6	2.6. Type of evaluation	C	2.7 Type of discipline	Optional	

3. Total estimated time (hours/semester of didactic activities) 
3.1 Hours per week 	4	Of which: 3.2 course	2	3.3 seminar/laboratory	1 lab+
1 project	
3.4 Total hours in the curriculum 	56	Of which: 3.5 course	28	3.6 seminar/laboratory	28	
Time allotment:	hours	
Learning using manual, course support, bibliography, course notes	20	
Additional documentation (in libraries, on electronic platforms, field documentation) 	10	
Preparation for seminars/labs, homework, papers, portfolios and essays	20	
Tutorship	5	
Evaluations	14	
Other activities: ..................		
3.7 Total individual study hours 	69	
3.8 Total hours per semester	125	
3.9 Number of ECTS credits	5	

4. Prerequisites (if necessary)
4.1. curriculum	•		
4.2. competencies	•		

5. Conditions (if necessary)
5.1. for the course	•		
5.2.  for the seminar /lab activities	•	Laboratory with computers; .NET environment;	

6. Specific competencies acquired 
Professional competencies	•	Knowledge, understanding and use of basic concepts of theoretical Computer Science
•	Ability to permanently learn, understand and apply the most recent scientific results in the field of Computer Science
•	Ability to work independently and/or in a team in order to solve problems in defined professional contexts.	
Transversal competencies	
•	The student will know what makes Business Intelligence systems different from transaction systems, how to integrate data into Data Warehouses, how to build and load information into an OLAP database, dimensional modelling concepts, querying OLAP cubes, data mining concepts and BI application development steps.	

7. Objectives of the discipline (outcome of the acquired competencies)
7.1 General objective of the discipline
	•	The student will get familiar with Business Intelligence concepts and applications	
7.2 Specific objective of the discipline
	•	The student will know what makes Business Intelligence systems different from transaction systems, how to integrate data into Data Warehouses, how to build and load information into an OLAP database, dimensional modelling concepts, querying OLAP cubes, data mining concepts and BI application development steps.	

8. Content
8.1 Course	Teaching methods	Remarks	

1. Business Intelligence foundations
	
Exposure, description, explanation, examples, discussion of case studies		

2. Online transaction processing (OLTP)
	
Exposure, description, explanation, examples, discussion of case studies		

3. Data warehouses and data integration (managing very large data warehouses)
	
Exposure, description, explanation, examples, discussion of case studies		

4. Online analytical processing (OLAP)
	
Exposure, description, explanation, examples, discussion of case studies		

5. Dimensional modeling
	
Exposure, description, explanation, examples, discussion of case studies		

6. MDX query language
	
Exposure, description, explanation, examples, discussion of case studies		

7. Data mining
	
Exposure, description, explanation, examples, discussion of case studies		

8-10. BI development steps (justification, planning, business analysis, design, construction, deployment)
	
Exposure, description, explanation, examples, discussion of case studies		

11. Managing changing data
	
Exposure, description, explanation, examples, discussion of case studies		

12. Real-time BI – case study
	
Exposure, description, explanation, examples, discussion of case studies		

13-14. Student presentations

Bibliography

John C. Hancock, Roger Toren, Practical Business Intelligence with SQL Server 2005, Addison Wesley Professional, 2006.
Larissa T. Moss, Shaku Atre, Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications, Addison Wesley Professional, 2003.
Ralph Kimball, Margy Ross, The Data Warehouse Toolkit. The Complete Guide to Dimensional Modeling, Wiley Computer Publishing, 2002.
Brian Larson, Delivering Business Intelligence with Microsoft SQL Server 2005, McGraw-Hill/Osborne, 2006.
Jay Liebowitz, Strategic Intelligence. Business Intelligence, Competitive Intelligence, and Knowledge Management, Auerbach Publications, 2006.
Lynn Langit, Foundations of SQL Server 2005 Business Intelligence, Apress, 2007.
	
8.2 Laboratory	Teaching methods	Remarks	
	
Practical projects		

1. SQL Server			

2. Building a Data Warehouse			

3. Data integration process			

4. Building an online analytical processing database (OLAP)			

5-6. Reporting Services			

7. Student presentations			
			
Bibliography

John C. Hancock, Roger Toren, Practical Business Intelligence with SQL Server 2005, Addison Wesley Professional, 2006.
Larissa T. Moss, Shaku Atre, Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications, Addison Wesley Professional, 2003.
Ralph Kimball, Margy Ross, The Data Warehouse Toolkit. The Complete Guide to Dimensional Modeling, Wiley Computer Publishing, 2002.
Brian Larson, Delivering Business Intelligence with Microsoft SQL Server 2005, McGraw-Hill/Osborne, 2006.
Jay Liebowitz, Strategic Intelligence. Business Intelligence, Competitive Intelligence, and Knowledge Management, Auerbach Publications, 2006.
Lynn Langit, Foundations of SQL Server 2005 Business Intelligence, Apress, 2007.	

9. Corroborating the content of the discipline with the expectations of the epistemic community, professional associations and representative employers within the field of the program

•	The course exists in the studying program of all major universities in Romania and abroad;
•	The content of the course is considered the software companies as important for average programming skills

10. Evaluation
Type of activity	10.1 Evaluation criteria	10.2 Evaluation methods	10.3 Share in the grade (%)	
10.4 Course	- know the basic principle of the domain;
	Written exam	50%	
10.5 Lab activities	- Business Intelligence applications 	Laboratory work 	50%	
				
10.6 Minimum performance standards	

•	At least grade 5 at both written exam and laboratory work.	

Date				Signature of course coordinator 	Signature of seminar coordinator
24.09.2012			Lect. Dr. Anca Andreica		Lect. Dr. Anca Andreica

Date of approval  					  Signature of the head of department	
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