Business intelligence

Course: Management of Organizations and Administration

Structural unit: Faculty of Economics

Title
Business intelligence
Code
ВК 3.2.10
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
4
Learning outcomes
Identify problems in the organization and justify methods for solving them. Plan the activities of the organization in strategic and tactical sections. Have the skills to make, justify and ensure the implementation of management decisions in unpredictable conditions, taking into account the requirements of current legislation, ethical considerations and social responsibility. Organize and carry out effective communication within the team, with representatives of various professional groups and in the international context. Identify and classify new tasks in the field of management, describe, analyze and evaluate relevant objects, phenomena and processes, choose the best methods for their study. Apply modern methodological and methodological tools for managing consulting projects, justify management decisions for the development, implementation and monitoring of consulting changes in the client organization.
Form of study
Full-time form
Prerequisites and co-requisites
1. A prerequisite for successful mastering of the subject is the preliminary preparation of students in economics (macro and microeconomics) and computer science, subjects "Insurance", "Risk management", "Finance" and others. 2. Knowledge of basic fundamentals of economics, finance, management of computer science.
Course content
This course provides an introduction to business intelligence, including the processes, methodologies, infrastructure and current practices that are used to transform business data into useful information and support business decision-making. Business analytics requires knowledge of the basics of the data storage and retrieval process, so this course examines logical data models for both database management systems and data warehouses. The subject of study of the discipline are theoretical and practical provisions of business process analysis.
Recommended or required reading and other learning resources/tools
1. A Guide to the Business Analysis Body of Knowledge (BABOK Guide) // International Institute of Business Analysis, Canada. – 2009. – v. 2.0. – 264p. 2. Thomas H. Davenport and Jeanne G. Harris. Competing on analytics: the new science of winning. // HBS Publishing Corporation. – 2017.- 218pp 3. Data Mining Techniques for Marketing, Slaes and Customer Relationship Management / Michael J.A. Berry, Gordon S. Linoff. – Wiley Publishing, Inc, 2011. – 3nd ed. – 643p. 4. Data Mining: Concepts and Techniques / Han J., Kamber M. – Elsevier Inc, 2011. – 2nd ed. – 745p. 5. Management Information Systems / Kenneth C. Laudon, Jane P. Laudon. – Pearson Education, Inc, 2014. – 10th ed. URL:repository.dinus.ac.id/docs/ajar/Kenneth_C.Laudon%2CJane_P_.Laudon_Management_Information_Sysrem_13th_Edition_.pdf
Planned learning activities and teaching methods
Problem-oriented learning: lectures; seminars; discussion; consideration of practical situations; performance of situational tasks; performance and presentation of group and individual tasks; consultations; independent work
Assessment methods and criteria
The semester number of points is formed by the points received by the student in the process of mastering the material on all topics of the content modules and performing all these individual analytical and computational tasks. The final control is carried out in the form of a written test, which is evaluated with a maximum of 20 points and is conducted in one of the last seminars in the discipline. The final grade in the student's discipline is presented based on the results of work during the semester as the sum of points obtained during the academic semester, including points obtained for independent work and the final test.
Language of instruction
English

Lecturers

This discipline is taught by the following teachers

Department of Insurance, Banking and Risk Management
Faculty of Economics

Departments

The following departments are involved in teaching the above discipline

Department of Insurance, Banking and Risk Management
Faculty of Economics