Nov 05, 2025  
2024-2025 Catalog 
    
2024-2025 Catalog [ARCHIVED CATALOG]

DBMS 110 - Introduction to Data Analytics


PREREQUISITES: Demonstrated readiness for college-level English and demonstrated readiness in QUANT MATH or STEM MATH - Route 2.
PROGRAM: Data Analytics
CREDIT HOURS MIN: 3
LECTURE HOURS MIN: 3
TOTAL CONTACT HOURS MIN: 48
DATE OF LAST REVISION: Fall 2023

Introduces students to the basic concepts of databases including the types of databases, the general database environment, and the importance of data to the business world. Discussion with hands-on activities will include database design, normalization of tables, and development of tables, queries, reports, and applications. Students will be familiarized with use of the ANSI Structured Query Language. Discussions will include database administration and data maintenance. Students will be introduced to data concepts such as data warehousing, data mining, data visualization, data analysis, and big data. Students will be required to demonstrate skills such as team building, work ethic, communications, documentation, and adaptability.

MAJOR COURSE LEARNING OBJECTIVES: Upon successful completion of this course, the student will be expected to:

  1. Identify, define or describe the types and nature of databases in a business setting.
  2. Categorize data integrity and security requirements.
  3. Compare and contrast the general structure and organization of relational, hierarchical, network database structures, and non-relational databases.
  4. Discover unstructured data techniques including Key-pair and JSON.
  5. Demonstrate an understanding of the relational data model.
  6. Describe the field names, field types, and relationships among tables.
  7. Demonstrate an understanding of normalization techniques in the design of databases utilizing 1NF, 2NF, & 3NF.
  8. Retrieve, insert, update, and manipulate data using SQL commands without the use of advanced generative tools.
  9. Express the concepts and use of big data, data warehousing, and data mining.


COURSE CONTENT: Topical areas of study include -
  • Creating and Managing Data
  • Multiple Table Queries
  • Introduction to Database Management
  • Database Design Methodology
  • Database Design Normalization
  • Data Security and Integrity
  • ANSI Structured Query Language (SQL)
  • Database Definition Language (DDL)
  • Data Dictionaries
  • Business Intelligence, Data Warehousing and Mining
  • Data Sources & Streams
  • 1NF, 2NF, 3NF, and higher normal forms
  • Primary and Foreign Key Relationships
  • Key-pair and JSON
  • Define and describe higher normal forms
  • Composite Keys
  • Stored procedures, triggers, views and functions
  • Explore job opportunities in data analytics
  • Entity Relationship Diagrams
  • Conceptual Data Modeling
  • Database Manipulation Language (DML)

 
Course Addendum - Syllabus (Click to expand)