CTS 2455 - Data Modeling and Logical Design

College of Computer & Information Technology

Credit(s): 3
Contact Hours: 47
Effective Term Fall 2020 (580)

Requisites

Prerequisite CTS 2433 with a minimum grade of C

Course Description

This is a foundational course in which students will extend knowledge beyond the physical storage of data to the modeling of the environment that will ultimately become a database. The focus is on the logical design of that environment. Topics covered will include the architecture and components of a database, entity-relationship modeling, enhanced entity-relationship modeling, and the relational data model. Additional coverage will encompass database normalization to include functional dependencies and the transition of the model from logical to physical form.

Learning Outcomes and Objectives

  1. Students will translate business requirements into logical data models that are ready to be implemented into physical databases by:
    1. classifying the characteristics of a database system.
    2. identifying the difference between data, information, and metadata.
    3. identifying relevant data elements.
    4. creating the appropriate queries to add logical data entities as physical database objects.
  2. Students will construct fully attributed, third normal form entity relationship models (ERDs) that are free from update anomalies by:
    1. listing entity types and attributes.
    2. classifying data integrity constraints.
    3. categorizing relationship types.
    4. listing the characteristics of a relation.
    5. defining normalization and its different forms.
    6. illustrating the presentation layer ER model.
  3. Students will provide examples of insertion, deletion, and modification anomalies that can result from errors and inconsistencies in logical data models by:
    1. evaluating data modeling errors.
    2. explaining deletion rules for intra-entity class relationships.
    3. validating a conceptual design.
  4. Students will identify and explain important logical data modeling aspects by:
    1. defining the concept of unique identifiers.
    2. distinguishing between primary and foreign keys.
    3. outlining the implications of composite keys and attributes.
    4. defining referential integrity and cardinality.
    5. contrasting functional dependencies and transitive dependencies.
  5. Students will investigate higher level data modeling concepts and theories by:
    1. contrasting top-down and bottom-up data modeling.
    2. describing object-oriented modeling.
    3. defining semantic modeling.
    4. examining relational algebra in constructing data queries.

Criteria Performance Standard

Upon successful completion of the course the student will, with a minimum of 70% accuracy, demonstrate mastery of each of the above stated objectives through classroom measures developed by individual course instructors.

History of Changes

C&I Approval: , BOT Approval: , Effective Term: Fall 2018 (550).
C&I Approval: 02/21/2020, BOT Approval: 03/17/2020, Effective Term: Fall 2020 (580)

Related Programs

  1. Business Analyst Specialist (ANLST-ATC) (625) (Active)
  2. Data Science (DATSCI-AS) (640) (Active)