Students at desks have classroom discussion.

Data Analytics Track

Combining the knowledge and training for analytically focused careers in business with the programming skills necessary for working with data.

The emphasis of the data analytics track at Saint Mary's is on applications of data analysis, business forecasting, modeling, operations management, market analysis, and project management techniques. The student in this major will learn programming and information technology skills to provide information for decision support systems.

Career Options

Graduates who possess a degree in the data analytics track are prepared for professional positions in business development, marketing, and financial or business analysis. 

High School Preparation

High school coursework that will support a student in his or her pursuit of a degree in the data analytics track includes experience in Economics, Mathematics, and Calculus.

Enhance Your Experience

Students who earn a degree in this track will oftentimes pursue a double major or minor in business, mathematics, or marketing

Degree Requirements

A. Computer Data Science Core

CS101 Computer Science Fundamentals (3 cr.)

This course provides a foundation in computing and algorithmic principles. Students are introduced to the basic conceptual building blocks of computer hardware and software systems. The tools and principles of algorithmic problem solving and systems design are explored. In the second half of the semester, students gain experience with simple programming challenges.  Credit is not granted for this course and CS106.

CS110 Computer Science I: Introduction to Programming (3 cr.)

This course introduces students to the practice of software development. Students learn the fundamentals of programming, algorithm development, and basic design principles.

CS111 Computer Science I Laboratory (1 cr.)

The laboratory course complements CS110 lectures.

CS210 Computer Science II: Advanced Programming and Data Structures (4 cr.)

This course is a continuation of CS111. CS210 expands on the programming techniques covered in CS1, adding discussion of recursion and data structures such as lists, stacks, queues, balanced trees, graphs and heaps. Specific algorithms that use these structures efficiently and general algorithm techniques and their analysis are also covered.

CS220 Discrete Mathematics (3 cr.)

This course provides the theoretical foundation of modern computer hardware and software. It provides that foundation in the form of mathematical tools and concepts geared toward computer science applications. Topics covered include: logic and set theory; functions and relations; simple algorithm analysis; and an introduction to graph theory.

B. All of the following:

BU243 Business Computer Applications (3 cr.)

This course provides in-depth coverage of Microsoft Excel and Access in the context of business applications. Excel topics include formulas and functions, charting, large datasets, pivot tables and what-if analysis. Access topics include relational database concepts, database design, basic query construction, and report generation. This course combines on-line and hands-on learning.

BU351 Information Systems for Business Intelligence (3 cr.)

This course focuses on the fundamentals of information systems and their foundational technologies as they can be used for business analysis and intelligence. Areas studied will include hardware, operating systems, database systems, knowledge management, decision support systems, and networked computing concepts. Data oriented techniques for business intelligence and decision making are introduced.

BU352 Data Analysis and Business Modeling (3 cr.)

This course is designed to introduce the concept of business analytics.  Analytics helps businesses make better decisions by using sound judgment and data.  This is a skill development class that explores how statistics are used in business.  Students in this course will leave with a specialized skillset used in a variety of roles within an organization.

BU354 Data Mining for Decision Making (3 cr.)

This course provides both the theoretical and practical knowledge of data mining topics. Students will have the opportunity to work with a number of exercises to practice and understand the uses of data mining in business organizations. Students will complete a data mining project as part of the course requirements.

BU420 Business Analytics (3 cr.)

This course will examine methods that have been studied in previous Business Intelligence major courses and those from the business core proven to be of value in recognizing patterns and making predictions from an applications perspective.  Course learning will involve utilizing a variety of software to aid in the review of analytical cases to improve understanding of enterprise level analytics.  Students will build a data warehouse, using data profiling and quality skills, and lifecycle models introduced in the course. 

C. One of the following:

BU469 Business Capstone Project (3 cr.)

The topics and projects for this course vary according to the needs and interests of business majors.

BU496/497 Internship: Business (1-17 cr.)

An opportunity for qualified juniors or seniors to participate in a field experience under the guidance and supervision of competent professionals.