Data Analytics Bachelor's Degree

View courses for our Data Analytics Bachelor's degree. Download the course catalog for more information.

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Course listings are subject to change. Please see our course catalog and/or addendum for most current listings.

Data Analytics Bachelor's Degree Course List

General Education Courses

Upper Division

Communication (Select 2 courses)

Humanities (Select 1 course)

Math/Natural Sciences (*Required course, select 1 additional course)

  • Inferential Statistics and Analytics

In this course students will be introduced to statistical methods used for predictive analytics. They will continue to build on their previous statics knowledge while strengthening their abilities to analyze and solve real-life problems using statistical methods. Topics may include, but are not limited to, estimation, hypothesis testing, correlation and regression, chi-square tests, and analysis of variance.

Prerequisite:Passing grade in Developmental Education coursework or placement determined by Rasmussen College entrance placement exam

Course ID: STA 3215*
Credits: 4

Social Sciences (Select 1 course)

Major and Core Courses

Upper Division

  • Fundamentals of Enterprise Architecture
  • Introduction to Business Intelligence
  • Emerging Trends in Technology
  • Business Project Management
  • Enterprise Resource Reporting
  • Operations Management
  • Introduction to Data Analytics
  • Foundations of Analytics Platforms, Environments, and Software
  • Introduction to Scripting
  • Introduction to Data Visualization
  • Data Elements
  • Applied Business Intelligence
  • Advanced Analytics Platforms, Environments, and Software
  • Data Quality in Analytics
  • Data Analysis and Optimization
  • Data Visualization Implementation and Communication
  • Data Analytics Capstone

This course is the study of business enterprise analysis, design, planning and implementation. It places focus on working with stakeholders, modeling business data flows and interfaces, determining the information security risk for an organization, and re-engineering business processes. Topics include current software development methodologies, business process modeling, and enterprise information security methodologies. This course will prepare students to work with stakeholders to ensure that information technology is in alignment with the goals of the business.


Course ID: CDA 3315C
Credits: 4

This course is the study of the skills and techniques for analyzing business performance data to provide support for business planning. It places focus on using query development, reporting, and analytical tools to help guide business decision-making. Topics include statistical analysis, basic database design, and business process modeling. This course will prepare students to utilize information to support decision-making.


Course ID: CTS 3265C
Credits: 4

This course is the study of emerging technologies. It places focus on technology impact on business and society in general. Topics include the relationship between emerging technologies and business opportunities, analysis of costs and savings of implementing particular technologies, legal and ethical issues affecting technology, challenges of adapting new technologies, and impacts of technology.


Course ID: CTS 4557
Credits: 3

This course provides students with the essential elements and foundational standards used to manage projects, programs and portfolios in any organization. Students will develop project scope and scheduling skills as well as assess program bidding and proposal processes. They will evaluate the impact of scope definition, and explore how to manage teams, expectations and project stakeholders.


Course ID: GEB 3422
Credits: 4

In this course students will develop an understanding of advanced enterprise resource reporting and business intelligence and how businesses can use them to support decision-making. Major electronic techniques and tools for classifying, segmenting, and analyzing business information will be examined. Students will learn how to integrate enterprise resource tools into standard business processes.


Course ID: IDC 3152
Credits: 4

In this course students examine the operations function of managing people, information, technology, materials, and facilities to produce goods and services. Specific areas covered will include: designing and managing operations; purchasing raw materials; controlling and maintaining inventories; and producing goods or services that meet customers' expectations. Quantitative modeling will be used for solving business problems.


This course is offered in a competency-based format for some programs.

Course ID: MAN 3504
Credits: 4

This course is an introduction to the concepts and tools used in current analytics practices. Students will be able to identify common tools, terms, and ideas. Topics covered will include visualization, data quality, platforms, and scripting.


Course ID: QMB 3000
Credits: 4

This course is the study of different types of environment. It places focus on developing and deploying Extract Transform Load (ETL) jobs. It also includes topics related to various types of analytics tools. This course will prepare the student for development ETL jobs in an enterprise environment. The student will also learn about the various analytic tools.


Course ID: QMB 3100
Credits: 4

This course serves as an introduction to the scripting process as it relates to data extraction and transformation processes.


Course ID: QMB 3200
Credits: 4

This course explores data visualization tools and techniques. It emphasizes the best ways to communicate data to the intended audience. Students learn about tools that aid in visualizing data and how to develop objective depiction of data using an editorial thinking approach. This course will prepare students for the challenges of having to analyze data and communicate results to audiences with various skill levels and preferences.


Course ID: QMB 3300
Credits: 4

This course reviews the concepts, standards, and functions used to identify data elements necessary for an efficient data preparation process.

Prerequisite:QMB 3200 Introduction to Scripting

Course ID: QMB 4000
Credits: 4

This course allows students to apply skills and techniques for analyzing existing business performance data to provide support for business planning. It places focus on planning an end-to-end business intelligence process, platform, database, and analytical tool usage. Students will learn about processing and analyzing data, quality assurance and regulatory adherence, and preparing data for consumption. Students will create visualizations to help guide business decision-making.

Prerequisite:CTS 3265C Introduction to Business Intelligence

Course ID: QMB 4100
Credits: 4

This course prepares the student for advanced analytics. It places focus on developing and deployed Extract Transform Load (ETL) jobs for large data sets. Topics will include how to configure the environment to run the advanced analytic job. It places focus on real-time analytics as well. This course will prepare students for developing advanced analytics and ETL job. It also prepares students about how to deploy the advanced analytics in the enterprise environment.

Prerequisite:QMB 3100 Foundations of Analytics Platforms, Environments, and Software

Course ID: QMB 4200
Credits: 4

Quality data allows for quality analysis. In this course, students will learn how to identify common types of data quality issues including missing data, incorrect data, outliers, normalization, and duplication. This course will prepare students to prepare data for analytics projects.


Course ID: QMB 4300
Credits: 4

This course will allow students to run data extracts and scripts to demonstrate a complete data analysis process, while requiring the identification and application of data element requirements, scripting modifications, and preparation techniques that could improve analysis results.

Prerequisite:QMB 4000 Data Elements; QMB 4300 Data Quality in Analytics

Course ID: QMB 4400
Credits: 4

This course focuses on the study of data sets which relate to meeting client needs. It includes methods used to evaluate data such as benchmarking, scoring, and ranking. Students learn the difference between correlation and causation. Students will explore techniques for visualizing both quantitative and qualitative data. This course will prepare students with the skills to derive business insights and make meaningful inferences from data sets.

Prerequisite:QMB 3300 Introduction to Data Visualization

Course ID: QMB 4500
Credits: 4

This course allows students to demonstrate their skills and techniques for analyzing generalized business data to provide support for business planning. It places focus on planning an end-to-end business analytics process; platform, database, and analytical tool usage; processing and analyzing data; quality assurance and regulatory adherence; preparing data for consumption; and visualization creation to help guide business decision-making.


Course ID: QMB 4900
Credits: 3

Total Program Credits

Transferred Lower Division Credits: 90

Upper Division General Education Credits: 24

Upper Division Major/Core Credits: 66

Total Bachelor's Degree Credits: 180

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