ECTS - Data Warehousing and Mining
Data Warehousing and Mining (ISE314) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Data Warehousing and Mining | ISE314 | 6. Semester | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| CMPE341 |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | The objectives of this course are to introduce and describe data warehousing steps and methods for accessing and analyzing warehouse data; and to introduce the basic concepts and rule mining techniques and develop skills of using recent data mining software for solving practical problems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Data warehousing fundamentals, planning, design and implementation and administration of data warehouses, data cube computation, OLAP query processing; fundamentals of data mining and relationship with data warehouse and OLAP systems; association rule mining; algorithms for clustering, classification and rule learning. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction to data warehousing | Chapter 1(Textbook 1) |
| 2 | Introduction to data mining | Chapter 1 (Textbook 1) |
| 3 | Data, measurements, and data preprocessing | Chapter 2 (Textbook 1) |
| 4 | Data warehousing and online analytical processing (OLAP) | Chapter 3 (Textbook 1) |
| 5 | Pattern mining: basic concepts and methods | Chapter 4 (Textbook 1) |
| 6 | Pattern mining: basic concepts and methods (cont.) | Chapter 4 (Textbook 1) |
| 7 | Classification: basic concepts and methods | Chapter 6 (Textbook 1) |
| 8 | Classification: basic concepts and methods (cont.) | Chapter 6 (Texbook 1) |
| 9 | Cluster analysis: basic concepts and methods | Chapter 8 (Textbook 1) |
| 10 | Cluster analysis: basic concepts and methods (cont.) | Chapter 8 (Textbook 1) |
| 11 | Outlier detection & Project Discussions | Chapter 11 (Textbook 1) |
| 12 | Data warehousing and mining practical applications-1 | Applications on software |
| 13 | Data warehousing and mining practical applications-2 | Applications on software |
| 14 | Data warehousing and mining practical applications-3 | Applications on software |
| 15 | Final Examination Period | Review of topics |
| 16 | Final Examination Period | Review of topics |
Sources
| Course Book | 1. Han, J., Kamber, M. & Pei, Jian (2023) Data Mining: Concepts and Techniques (4th edition) Morgan Kaufmann, Elsevier: Cambridge. MA |
|---|---|
| Other Sources | 2. Bhatia, P. (2019) Data Mining and Data Warehousing: Principles and Practical Techniques Cambridge: Cambridge, UK |
| 3. Taniar, D. & Rahay, W. (2021) Data warehousing and analytics: Fueling the Data Engine Springer Nature: Switzerland AG | |
| 4. Sharda, R., Delen, D. & Turban, E. (2020) Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support (11th edition / Global edition) Pearson, London, UK |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | 1 | 15 |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 3 | 10 |
| Presentation | - | - |
| Project | 1 | 20 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 25 |
| Final Exam/Final Jury | 1 | 30 |
| Toplam | 7 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Gain sufficient knowledge in mathematics, science and computing; be able to use theoretical and applied knowledge in these areas to solve engineering problems related to information systems. | |||||
| 2 | To be able to identify, define, formulate and solve complex engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Designs a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; applies modern design methods for this purpose. | X | ||||
| 4 | To be able to develop, select and use modern techniques and tools required for the analysis and solution of complex problems encountered in information systems engineering applications; to be able to use information technologies effectively. | X | ||||
| 5 | Designs and conducts experiments, collects data, analyzes and interprets results to investigate complex engineering problems or research topics specific to the discipline of information systems engineering. | X | ||||
| 6 | Can work effectively in disciplinary and multidisciplinary teams; can work individually. | |||||
| 7 | a. Communicates effectively both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. b. Knows at least one foreign language. | |||||
| 8 | To be aware of the necessity of lifelong learning; to be able to access information, to be able to follow developments in science and technology and to be able to renew himself/herself continuously. | |||||
| 9 | a. Acts in accordance with the principles of ethics, gains awareness of professional and ethical responsibility. b. Gains knowledge about the standards used in information systems engineering applications. | |||||
| 10 | a. Gains knowledge about business life practices such as project management, risk management and change management. b. Gains awareness about entrepreneurship and innovation. c. Gains knowledge about sustainable development. | |||||
| 11 | a. To be able to acquire knowledge about the universal and social effects of information systems engineering applications on health, environment and safety and the problems of the era reflected in the field of engineering. b. Gains awareness of the legal consequences of engineering solutions. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | 1 | 4 | 4 |
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 2 | 32 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 10 | 10 |
| Report | |||
| Homework Assignments | 3 | 2 | 6 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 125 | ||