Introduction to Database Management Systems

Course
Course Catalog URL: 
http://catalog.iastate.edu/azcourses/com_s/
Identifier: 
COM S 3630
Professor(s): 
Qi Li,
Regis Kopper

Last Updated: Fall 2024

Offered during Fall and Spring Semesters each year. 

  1. Credits and contact hours: 3 credits
  2. Instructor’s or course coordinator’s name: Qi Li, Regis Kopper
  3. Text book, title, author, and year: None required
  4. Other supplemental materials: Database Management Systems, 3rd edition, R. Ramakrishnan and J. Gehrk

Specific course information

  1. Brief description of the content of the course: Relational, object-oriented, semistructured and query languages. SQL, XML, and NO-SQL. Database design using entity-relationship model, data dependencies, and relational database design. Application development in SQL-like languages and general-purpose host languages with application program interfaces and a commonly used Object Relational Mapping framework. Web application development. Programming Projects.
  2. Prerequisites or co-requisites: Minimum of C- in COM S 2280 and MATH 1650; ENGL 2500
  3. Required, elective, or selected elective? Selected Elective

Specific goals for the course

  1. Specific outcomes of instruction:
    1. Design and implement database applications using commercial DBMS
    2. Understand the implementation of a typical DBMS

Brief list of topics to be covered

  • Introduction:
    • The largeness of information and its implications on the organization of disk in terms of pages in kilobyte range rather than words consisting of a few bytes. Layered architecture of databases and varieties of users.
  • Query languages in different paradigms and hybrid languages
    • Foundational language relational algebra and how it gives rise to user-oriented language SQL. How SQL is reincarnated as OQL and XQuery in object-oriented and XML data models.
  • Hybrid languages
    • JDBC (Java Database Connectivity) as a hybrid of algebraic and general-purpose languages.
  • Storage and efficient retrieval of data
    • Storing information in pages on a disk, indexes, algebraic optimization and Query processing.
  • Schema design
    • Schema design using (a) Entity-relationship model and (b) data dependencies
  • Relational, object-oriented, and semi-structured (XML) data models
  • Information integration: Data warehousing