Data Analytics Undergraduate Degree Curriculum: A Comprehensive Overview

In today's data-driven world, the ability to transform raw numbers into actionable insights is a highly sought-after skill. A data analytics undergraduate degree curriculum equips students with the knowledge, skills, and experience necessary to thrive in this dynamic field. This article provides a comprehensive overview of what such a curriculum entails, covering various aspects from admission requirements to career opportunities.

Introduction

A Bachelor of Science in Data Analytics is designed to provide students with a fundamental understanding of statistical reasoning and methodology. The curriculum trains students to apply this knowledge to the collection and analysis of data, preparing them for careers in a highly technological society where science and decision-making are increasingly driven by the rapid expansion in the quantity and availability of data. This interdisciplinary program brings together computer science, mathematics, and statistics with a specific area of focus chosen from a variety of data-generating majors and minors.

Core Competencies and Skills

The core of a data analytics curriculum focuses on principles that are fundamental to all areas of data analytics. Students gain organizational and technical competencies to implement data gathering, cleansing, integration, and modeling tasks, as well as data asset analysis for business applications. The curriculum emphasizes the fundamentals of programming, databases, and statistical reasoning, ensuring students achieve proficiency in these areas.

Key skills developed in a data analytics program include:

Data Analysis: Conducting purposeful, real-world data analysis in the student's specialty area using knowledge from core areas of data analytics.
Data Management: Managing complex real-world data sets and extracting useful information in the student's specialty area.
Ethical Considerations: Identifying the ethical, policy, and security considerations and issues of working with data and how its use impacts society.
Communication: Communicating effectively to a non-technical audience what is learned from data, using oral, written reports, or data visualization techniques.

Curriculum Structure

A typical data analytics undergraduate degree requires the completion of 120 (or 128) credit hours. The curriculum is structured to provide a balance of general education, core data analytics courses, and specialized electives.

Read also: Data Theory at UCLA

The curriculum generally includes the following components:

Carolina Core Requirements (32-45 hours): These requirements cover essential skills such as effective communication, analytical reasoning, scientific literacy, and global citizenship.
College Requirements (15-18 hours): These include courses in social science and fine arts or humanities to provide a broad educational foundation.
Program Requirements (33-49 hours): This section includes supporting courses in statistics and ethics, a minor or additional major, and elective courses.
Major Requirements (24 hours): This includes core major courses and major electives that focus on specific areas of data analytics.

Core Courses

The core courses in a data analytics program typically cover the following topics:

Statistical Methods for Data Analytics
Big Data Analytics
Computing for Data Science
Visualization Tools

Electives and Specializations

Students can choose electives to tailor their degree to their specific interests and career goals. These electives may include courses in:

Machine Learning
Geographic Information Systems (GIS)
Genomic Data Science
Data Mining
Database Systems in Information Technology
Digital Marketing & Social Media Analytics

Admission Requirements

Admission requirements for a data analytics undergraduate degree program vary depending on the institution. However, general requirements typically include:

First-Year Admission Requirements

A competitive score on the SAT Reasoning or ACT.
Graduation in the top percentage of high school class.
A minimum overall high school GPA in required competency courses.

Transfer Admission Requirements

A minimum number of credit hours after high school.
A minimum transfer GPA.
A competitive score on the SAT Reasoning or ACT (if applicable).

Global Experiences

As globalization continues to impact the way the world lives and works, international experiences have become vital for business data analytics students. Through international study and internships, students can gain valuable skills that employers are looking for, such as:

Communication and interpersonal skills
Flexibility
Motivation
A real-life perspective on business applications worldwide

International experiences can help students understand new perspectives in the use of data on an international scale. Students can leverage global opportunities and learning, which are great assets as students prepare for internships and share these unique experiences with recruiters.

Accelerated and Concurrent Programs

Some universities offer accelerated programs that allow students to expedite the completion of their degree. These programs have specific requirements that students must meet to be eligible for consideration. Students typically receive approval to pursue the accelerated master’s during the junior year of their bachelor's degree program.

Concurrent degrees allow students to pursue their own personal or professional interests, earn two distinct degrees, and receive two diplomas. To add a concurrent degree to an existing degree, students work with their academic advisor.

Career Opportunities

A data analytics degree opens doors to a wide range of career opportunities across various industries. The demand for employees with business analytics skills is strong. Graduates can become:

Data Analysts
Data Architects
Data Visualization Developers
Data Change Agents
Data Operators

Online Data Analytics Programs

Many universities offer data analytics programs in an entirely online format with multiple enrollment sessions throughout the year. Online programs provide flexibility for students who need to balance their studies with other commitments.

WGU's Bachelor of Science in Data Analytics is an all-online program that utilizes a ‘three-lever’ approach to data analytics, surgically incorporating programming, math, and business influence skills. The program is designed to help students learn to take data and turn it into meaningful stories that help leaders make decisions.

Curriculum Examples

WGU B.S. Data Analytics Sample Courses

Applied Algebra
Applied Probability and Statistics
Data Management - Foundations
Data Analytics - Applications
Introduction to Data Science
Data Analysis with R
Machine Learning
Big Data Foundations

Eastern Oregon University (EOU) B.S. Data Analytics Sample Courses

C/C++ Programming
Machine Learning
Geographic Information Systems (GIS)

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