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Course Description Course Name : Database Management and Decision Support Systems Course Code : EM-518 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Learning Outcomes of the Course : Learns the basics of database management and has the ability to design a database Learns different DBMSs such as SQL, Access Is aware of the importance of database design for the companies Learns how to design a DSS in order to support managers in effective decision making Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The objectives of this course are to: (1) teach principles of database design and manipulation, (2) explore the complicated issue of effective software support for many structured and semi-structured business decision problems. Topics include: conceptual, logical and physical database design; data dictionary; relational modeling; decision-support systems. Course Contents : Introduction to ER Model and Conceptual Design,The Relational Model and SQL DDL, Logical Model, SQL, Overview of Storage and Indexing,Schema Refinement, Functional Dependencies, Normalization , Physical Database Design, Database Tuning , Security and Authorization (21), Backup/Recovery, Decision Support Systems,Conceptual model of DSS, Applications of Decision Support Systems. Language of Instruction : English Work Place : Classroom , Lab   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction to database Reading handouts Discussion, lecture, brainstorming 2 ER Model and Conceptual Design, Reading handouts Discussion, lecture, brainstorming 3 The Relational Model and SQL Reading handouts Discussion, lecture, brainstorming 4 Storage and indexing Reading handouts Discussion, lecture, brainstorming 5 Normalization Reading handouts Discussion, lecture, brainstorming 6 Physical database design Reading handouts Discussion, lecture, brainstorming 7 Database Tuning Reading handouts Discussion, lecture, brainstorming 8 Security and Authorization Reading handouts Discussion, lecture, brainstorming 9 DBMS recovery and backup Reading handouts Discussion, lecture, brainstorming 10 Applications of DBMS Reading handouts Lab application 11 Midterm Read and review all the chapters included in the exam written mideterm exam 12 İntroduction to Decision Support Systems Reading handouts Discussion, lecture, brainstorming 13 Conceptual model of DSS Reading handouts Discussion, lecture, brainstorming 14 Applications of DSS Reading handouts Discussion, lecture, brainstorming 15 Project delivery and presentation Project preparatşon Project presentation 16/17 Final exam Read and review all the chapters included in the exam Written final exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Decision Support Systems and Expert systems, Efraim Turban  Database Management Systems, Third Edition Raghu Ramakrishnan, Johannes Gehrke ISBN: 0-07-246563-8 Publisher: McGraw-Hill Higher Education Pub. Date: 2003 Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 30     Homeworks/Projects/Others 2 70 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Understand, interpret and apply knowledge in his/her field domain both in-depth and in-breadth by doing scientific research in industrial engineering. 2 2 Acquire comprehensive knowledge about methods and tools of industrial engineering and their limitations. 4 3 Work in multi-disciplinary teams and take a leading role and responsibility. 2 4 Identify, gather and use necessary information and data. 5 5 Complete and apply the knowledge by using scarce and limited resources in a scientific way and integrate the knowledge into various disciplines. 3 6 Keep up with the recent changes and applications in the field of Industrial Engineering and analyze these innovations when necessary. 4 7 Work in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. 1 8 Analyze Industrial Engineering problems, develop innovative methods to solve the problems. 4 9 Have the ability to propose new and/or original ideas and methods in developing innovative solutions for designing systems, components or processes. 5 10 Design and perform analytical modeling and experimental research and analyze/solve complex matters emerged in this process. 3 11 Follow, study and learn new and developing applications of industrial engineering. 3 12 Use a foreign language in verbal and written communication at least B2 level of European Language Portfolio. 4 13 Present his/her research findings systematically and clearly in oral and written forms in national and international platforms. 4 14 Understand social and environmental implications of engineering practice. 3 15 Consider social, scientific and ethical values in the process of data collection, interpretation and announcement of the findings. 3 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 5 70 Assesment Related Works     Homeworks, Projects, Others 2 20 40     Mid-term Exams (Written, Oral, etc.) 1 2 2     Final Exam 1 5 5 Total Workload: 159 Total Workload / 25 (h): 6.36 ECTS Credit: 6