The business analytics pathway focuses on applying data to inform decision-making in both public and private sectors.
The course content is regularly updated based on input from local employers to ensure students develop relevant, marketable skills. Graduates are prepared for entry-level analytical roles such as business intelligence analyst, marketing analyst, and human resources analyst, while also having the foundation to pursue further studies in business analytics.
This pathway is available 100% online and has on campus options as well for interested students.
This program transfers seamlessly to the University of New Hampshire College of Professional Studies online bachelor’s degree in business management: business analytics. Additional transfer options are available to students for business analytics and business administration at multiple local private and public colleges.
Career Tracks
An associate degree in data analytics – business analytics typically provides skills for supporting business decision-making with data. While this degree is shorter and more introductory than a four-year degree, it can sufficiently prepare you for employment in entry-level positions in analytics or related fields. Job titles attainable for an associate’s degree holder include:
- Marketing assistant
- Research assistant
- Data and reporting analyst
- Administrative assistant
- Sales analyst
A bachelor’s degree with a focus on business analytics gives graduates more advanced tools and techniques for data-driven decision-making. This is typically the entry point to mid-level roles in business analytics. Job titles typical of a bachelor’s degree level business analyst include:
- Supply chain analyst
- Business analyst
- Business intelligence analyst
- Data visualization specialist
- HR data analyst
- Financial analyst
- Operations research analyst
- Market research analyst
A master’s degree in business analytics (or a related field like Data Science or Business Intelligence) positions professionals for senior roles that require specialized knowledge, leadership, and the ability to manage complex business challenges. Examples of job titles at this level include:
- Chief Data Officer (CDO)
- Chief Analytics Officer
- Director of Business Intelligence
- Senior Business analyst
Business Analytics Pathway
FIRST YEAR – FALL SEMESTER
Course Code | Title | Class | Lab | CR |
ENGL101N | College Composition | 4 | 0 | 4 |
DATA101N | Introduction to Data Analytics | 2 | 2 | 3 |
MATH106N | Statistics I | 4 | 0 | 4 |
DATA105N | Data Mining | 2 | 2 | 3 |
BCPT119N | Software Applications | 2 | 2 | 3 |
|
|
| Semester Credits | 17 |
FIRST YEAR – SPRING SEMESTER
Course Code | Title | Class | Lab | CR |
CSCI130N CSCI207N BCPT213N | Databases – An Overview OR Database Design & Management OR Database Management: ACCESS | 2 | 2 | 3 |
ENGL109N ENGL103N | Public Speaking OR Professional Writing & Presentations | 3 | 0 | 3 |
DATA120N | Applied Data Analysis | 2 | 2 | 3 |
MATH206N DATA230N | Statistics II OR Business analytics | 4 | 0 | 4 |
Gen Ed | Behavioral Social Sciences OR Non-Behavioral Social Sciences | 3 | 0 | 3 |
|
|
| Semester Credits | 16 |
SECOND YEAR – FALL SEMESTER
Course Code | Title | Class | Lab | CR |
BUS101N BUS110N | Introduction to Business OR Principles of Management | 3 | 0 | 3 |
Gen Ed | Humanities/Fine Arts/World Languages | 3 | 0 | 3 |
Gen Ed | Natural or Physical Sciences |
|
| 4 |
ACCT101N | Financial Accounting 1 | 4 | 0 | 4 |
|
|
| Semester Credits | 14 |
SECOND YEAR – SPRING SEMESTER
Course Code | Title | Class | Lab | CR | |||
DATA205N | Data Visualization | 2 | 2 | 3 | |||
DATA210N | Data Wrangling | 2 | 2 | 3 | |||
ACCT102N | Financial Accounting 2 | 4 | 0 | 4 | |||
DATA220N | Applications of Machine Learning and Artificial Intelligence | 2 | 2 | 3 | |||
|
|
| Semester Credits | 13 | |||
TOTAL | 60 | CREDITS |
|
Upon the completion of the degree in Data Analytics, graduates will be able to:
- Identify data sources, types of data, and data structures, including structured and unstructured data.
- Remediate raw data as appropriate before analysis including cleaning and restructuring data using software tools and programming skills.
- Collect and combine data from multiple sources using database programming (SQL) and related skills.
- Use analytical tools to identify patterns and relationships in data sets including time trends, cluster analysis, association analysis, classification, and statistical associations and relations.
- Apply data analytics to address real-world problems and communicate results to stakeholders
- Visually communicate patterns and relations in data applying best practices of data visualization.
- Identify legal and ethical issues in analyzing data and adhere to ethical standards.
The data analytics degree program is open admissions and has no prerequisites for students to begin coursework. Students are required to have a computer meeting the technical specifications necessary to run analytical software. Most software packages used in the program are open source, provided by the college or available at nominal cost to students. When possible, freely available open educational resources are utilized in coursework thus minimizing student cost.
Contact us
Kimberly Seefeld, EdD
Professor and Program Coordinator
[email protected]
603.578.8900 Ext. 1554