Course Details

Return to Classes
Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
7BA458USE OF BUSINESS INTELLIGENCE3+0+03512.09.2025

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program BUSINESS ADMINISTRATION
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course Providing fundamental terminologies in Business Intelligence, Analytics and Data Science.
Outlining Descriptive Analytics, Predictive Analytics, and PrescriptiveAnalytics.
Course Content This course introduces data-oriented techniques for business intelligence. Business Intelligence architecture, Big Data, Business Analytics, and Enterprise Reporting are topics covered. In order to access and present data, form reports, conduct analysis SAP Business Information Warehouse, Business Objects, or similar tools are be utilized.
Course Methods and Techniques
Prerequisites and co-requisities ( BA303 )
Course Coordinator Associate Prof.Dr. Fatma Selen Madenoğlu selen.madenoglu@agu.edu.tr
Name of Lecturers Associate Prof.Dr. FATMA SELEN MADENOĞLU
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources


Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Quiz/Küçük Sınav 1 % 100
Total
1
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Ev Ödevi 4 23 92
Sınıf İçi Aktivitesi 14 1 14
Yüz Yüze Ders 14 3 42
Total Work Load   Number of ECTS Credits 5 148

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Define the terminology of Business Intelligence and Data Analytics.
2 Analyze business analysis.
3 Compose multi-dimensional data analysis
4 Apply analytical reporting functions available in an ERP system.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 An Overview of Business Intelligence, Analytics and Data Science
2 An Overview of Business Intelligence, Analytics and Data Science
3 Descriptive Analytics
4 SAP SA
5 SAP SAP
6 SAP
7 SAP
9 SAP
10 Predictive Analytics
11 Predictive Analytics
12 Prescriptive Analytics
13 Data Mining Process. Method and Algorithm
14 Data Mining Process. Method and Algorithm
15 Big Data and Analytics

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
C1 5 5 5 5 2 1 5 5 5 5
C2 5 5 3 5 3 1 5 5 5 5
C3 5 5 3 5 2 5 5 5 5
C4 5 5 2 5 4 3 3 5 5 5

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=79312&lang=en
Return to Classes