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 | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| CMPE341 |
| Course Language | English |
|---|---|
| Course Type | N/A |
| 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 1,2 (Textbook 1) |
| 2 | Dimensional data modeling | Chapter 2 (Textbook 2) |
| 3 | Building the data warehouse 1 | Chapter 6 (Textbook 1) |
| 4 | Building the data warehouse 2 | Chapter 6 (Textbook 1) |
| 5 | Building the data warehouse 3 | Chapter 6 (Textbook 1) |
| 6 | Data mining and data visualization 1 | Chapter 3 (Textbook 1) |
| 7 | Data mining and data visualization 2 | Chapter 3 (Textbook 1) |
| 8 | Data mining techniques: Clustering 1 | Chapter 5 (Other sources 3) |
| 9 | Data mining techniques: Decision trees 3 | Chapter 5 (Other sources 3) |
| 10 | Practical data warehousing and data mining 1 | Applications on software |
| 11 | Practical data warehousing and data mining 2 | Applications on software |
| 12 | Practical data warehousing and data mining 3 | Applications on software |
| 13 | Practical data warehousing and data mining 4 | Applications on software |
| 14 | Practical data warehousing and data mining 5 | Applications on software |
| 15 | Final Examination Period | Review of topics |
| 16 | Final Examination Period | Review of topics |
Sources
| Course Book | 1. George M. Marakas, “Modern Data Warehousing, Mining, and Visualization: Core Concepts”, Prentice Hall, 2003. |
|---|---|
| 2. R. Kimball and M. Ross, “The Data Warehouse Toolkit” , 2002, Wiley | |
| Other Sources | 3. Han J.W., Kamber M. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, 2006. |
| 4. Tan P.N., Steinbach M., Kumar V. Introduction to Data Mining. Addison Wesley, 2005. | |
| 5. Berry, M., J., A., & Linoff, G., S., (2000). Mastering data mining. New York: Wiley. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 1 | 30 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 3 | 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 | Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. | |||||
| 2 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose. | X | ||||
| 4 | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively. | X | ||||
| 5 | Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline. | X | ||||
| 6 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
| 7 | a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
| 8 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development. | |||||
| 9 | a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications. | |||||
| 10 | a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development. | |||||
| 11 | a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. 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) | |||
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 5 | 80 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 20 | 20 |
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 15 | 15 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 135 | ||