DATABASE MANAGEMENT SYSTEMS I

Course Description

At the end of this course, students are expected to have experience and knowledge on databases, database design and SQL. Introduction to DBMS (Definition, characteristics, levels of abstraction, advantages, query types), Relational database (relational model, database design), Relational Algebra, SQL, Data Manipulation Language (DML), nested queries, sub-queries, joins, grouping, row functions, aggregate functions, Data Definition Languages (DDL) with constraints like primary key, foreign key and case constraints will be covered. Also, database user management and user rights will be explained.

DATABASE MANAGEMENT SYSTEMS I

Evaluation Tools (Active Term)

Course outcomes

1. 01 Analyze a problem to design a relational database.
2. 02 recognize the fundamental concepts in relational theory
3. 03 implement relational theory to working knowledge of Oracle DBMS Server
4. 04 apply SQL for DML and DDL

Course Syllabus

Reference Books & Course Materials

1. 01 Elmasri & Navthe: Fundamentals of Database Systems, Addison Wesley, fifth ed., 2007.

Learning Outcomes

1. L01 To develop skills for designing and implementing a relational database SOLO 5
2. L01 To develop skills for designing and implementing a relational database SOLO 5
3. L02 Describe the fundamental concepts in relational theory SOLO 3
4. L02 Describe the fundamental concepts in relational theory SOLO 3
5. L03 Perform operations using query language using DBMS softwares SOLO 4
6. L03 Perform operations using query language using DBMS softwares SOLO 4
7. L04 Develop skills and understanding to create and modify tables in relational databases SOLO 5
8. L04 Develop skills and understanding to create and modify tables in relational databases SOLO 5

Program Outcomes

1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix