DATABASE MANAGEMENT SYSTEMS II

Course Description

Fundamental concepts and applications about DB architectures will be discussed like properties of popular databases, backup, recovery, replication and reverse engineering. Also, students will gain knowledge on transactions, indexes, PL/SQL, Triggers, stored, functions, stored procedures and cursors. Views, materialized views, query performance optimization, database application Development with a programming language and SQL injection will also explained. Case studies will cover the topics studies in this lecture.

DATABASE MANAGEMENT SYSTEMS II

Evaluation Tools (Active Term)

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Course outcomes

1. 01 To develop skills for database administration for database objects
2. 02 To give students an ability to clarify and apply the fundamental concepts in stored procedures/functions/triggers/materialized views
3. 03 To give students a working knowledge and ability to apply Oracle DBMS Server's PLSQL
4. 04 To enable students develop an application with DBMS

Course Syllabus

Reference Books & Course Materials

1. 01 Elmasri & Navathe "Fundementals of Database systems" 5th edition 2007
2. 02 Oracle PL/SQL: Expert Techniques for Developers and Database Administrators
3. 03 Database System Concepts

Learning Outcomes

1. L01 To develop skills for database administration for database objects,
2. L02 To give students an understanding of the fundamental concepts in stored procedures/functions/triggers/materialized views,
3. L03 To give students a working knowledge of Oracle DBMS Server's PLSQL,
4. L04 To enable students in the use of DBMS within an application.

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.

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