Database Technologies Minor

Catalog Year

2020-2021

Degree

Minor

Credits

20

Locations

Mankato

Accreditation

Program Requirements

Core

This course provides conceptual and logical tools for students planning to major in a computing-based major. Programming in a high-level language such as C++, Python, or Java, and the development of skills in abstraction, problem-solving, and algorithmic thinking are emphasized.

Prerequisites: MATH 112 or MATH 113 or MATH 115 or MATH 121

This course is a continuation of CIS 121. Students develop a basic knowledge of programming skills and object-oriented concepts, and use fundamental data structures such as lists, stacks, queues, and trees.

Prerequisites: MATH 113 or MATH 115 or MATH 121; and CS 110 or CIS 121 or IT 210

Introduction to database systems, entity relationship models, relational algebra, database design, data modeling, normalization, and conversion of business rules into relational model. Introduction to basic SQL including subqueries, joins, functions, sequences, triggers, views, and stored procedures.

Prerequisites: CIS 121 with a 3.0 or higher or an approved substitute.

Restricted Electives

Choose 8 Credit(s).

Extensive coverage of SQL, database programming, large scale data modeling, and database enhancement through reverse engineering. This course also covers theoretical concepts of query processing, and optimization, basic understanding of concurrency control and recovery, and database security and integrity in centralized/distributed environments. Team-oriented projects in a heterogeneous client server environment.

Prerequisites: CIS 380

This course covers science and study of methods of protecting data, and designing disaster recovery strategy. Secure database design, data integrity, secure architectures, secure transaction processing, information flow controls, inference controls, and auditing. Security models for relational and object-oriented databases.Variable

Prerequisites: CIS 350, CIS 440

The course explores big data in structured and unstructured data sources. Emphasis is placed on big data strategies, techniques and evaluation methods. Various data analytics are covered. Students experiment with big data through big data analytics, data mining, and data warehousing tools.

Prerequisites: CIS 223, CIS 440