Yes! Tell me more about Merrimack’s Business Analytics degree!

Online Masters in Business Analytics


Spend your time developing applicable skills you can use on the job the next day. The online Master of Science in Business Analytics degree from Merrimack College teaches students to solve problems and visualize data sets using the latest industry tools and analytical methods.

This business analytics degree is offered through a unique collaboration between the School of Science & Engineering and the Girard School of Business. Professors from both schools combine to help you learn to develop engineering skills needed to function as a business analyst along with the business acumen needed to translate data sets into actionable insights that can be presented to stakeholders.

The projects and assignments in the program curriculum were designed with input from an industry council to ensure that graduates are equipped with the business analytics skills that employers need. Be ready to meet the demands of a career in business analytics.

Merrimack College’s online Master of Science in Data Science and Master of Science in Business Analytics programs have been named in the Top 50 Best Value Online Big Data Programs 2018 by  Coming in at number 10 out of 50 programs, Merrimack’s top ranking was based on mid-career salary potential, U.S. News & World Report ranking, and program tuition.

Expected Growth Rate for Analyst Jobs
median salary for Senior Business Analyst
Top 0
ranked Best Job in America

Source: Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2016-17 Edition &, Obtained April 2017

Where Can Your Business Analytics Degree Take You?

Potential career paths for graduates of the Master of Science in Business Analytics include:

Senior Business Analyst

$82,323per year

Business Systems Analyst

$67,142per year

Sr Data Analyst

$76,209per year

Source:, Obtained May 2017

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Career Insights for Business Analytics

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Discover the Merrimack Difference


“As a new manager with expanding responsibilities at times I’m faced with resource constraints.  The Data Science program has given me the ability to support my team by taking on some of the analytic work when we have resource constraints.  Not only am I gaining a greater understanding of analytics, but I am able to apply my new knowledge every day in the workplace.”

WILL LINDSEY, Manager of Analytics, Blue Cross and Blue Shield of North Carolina

What Skills Will You Develop With a Business Analytics Degree?

To earn your Master of Science in Business Analytics degree, you will complete the 8 courses listed below for a total of 32 credit hours. Classes are offered through a collaboration between the School of Science & Engineering and the Girard School of Business ensure your skills in both coding/development and business are aligned as you learn. Students can finish their master’s degree taking courses over a period of 12-16 months

Foundations of Data Management course provides students exposure to fundamental data management skills used in modern information systems that support various operational and functional areas within a business organization. Topics covered in the course have an emphasis on how data is fundamentally identified, organized, described and managed as the most valued asset within an organization. Course emphasis is also on applied learning of concepts and skills for relational data modeling and querying. This course will help prospective Data Science and Analytic business professionals to develop and apply data management skills that will be essential to the success in subsequent coursework.

This course provides students with a foundation in basic statistical analysis, focusing primarily on descriptive univariate statistics. Topics addressed in this course include variables and their properties, measurement scales, descriptive analyses of continuous and categorical variables, Central Limit Theorem, univariate and bivariate estimation, and hypothesis testing logic and procedures. Students will be exposed to hands-on computational examples using R and SPSS as they learn how to apply the various statistical concepts covered in this course to real-life business situations.

This course introduces students to the fundamentals of exploratory data analyses, broadly defined here as review of the available/focal data, and extraction of descriptive characteristics with the goal of generating valid and reliable insights. The course covers the basic data due diligence and curation considerations, key data preparatory steps, and offers an overview of a general descriptive data analytical framework. Analytic approach-wise, the course addresses analyst-led exploration utilizing classical statistical techniques, as well as automated data mining applications, while addressing topics of statistical inference, statistical significance, and outcome validity and reliability. Lastly, the course combines conceptual overview of the focal concepts and statistical reasoning, while also providing hands-on introduction to the practical side of data exploration. The general instructional approach used in this course is one that casts exploratory data analyses in the context of the data –> information –> knowledge continuum that underpins extraction of decision-guiding insights out of the available data as a way of answering business questions.

This course will offer Business Analytics students with a broad base introduction to multivariate statistical methods, with particular emphasis on explanatory and predictive techniques. The commonly used dependence and interdependence techniques are discussed, including linear and logistic regression, decision trees and select machine learning approaches. The course is focused particularly on topics relating to technique selection, result interpretation and translation of analytic outcome into decision-guiding insights.

As data analytic technologies became more advanced, it became progressively easier and easier to execute sophisticated analyses; also, as the volume of the available data exploded, more and more analyses began making use of very large sample sizes. Those trends have a direct impact on the validity and reliability of outcomes of statistical analyses, the investigation of which is the focus of this course. More specifically, in this course the students will take a closer look at topics such as the impact of sample size on statistical significance, and the relationship between practical materiality of findings and the more abstractly framed statistical significance.

This course focuses on the effective communication of data analysis and its insights and implications. Students will learn the principles and techniques for information visualization and representation as well as verbal and written communication. Students will develop proficiency in several of the latest tools for visualization. Students will use real-world business scenarios to gain experience designing and building data visualization and communication.  Best practices will be highlighted and students will receive tailored individual coaching and feedback sessions to accelerate skill improvement.

This course introduces students to the current and emerging topics and considerations addressing the issue of data governance, usage and security; furthermore, this course also investigates the ethical and legal right and responsibilities of data analysts, and delves into questions that emerge from developing, storing, analyzing and using data.  Issues including intellectual property, data ownership, storage security and safeguards as well as the human impact of using data are investigated; case studies and scenario explorations in a range of industries from consumer products and retail to government and social justice are used to illustrate and apply the concepts discussed in class, with the goal of preparing students to manage these often grey issues during their career.

Digital marketing including social media and web-based advertising have fundamentally transformed how goods and services are marketed and sold today. The strategic aspects, performance metrics and business value of social media and digital marketing analytics will be explored. Each student will develop a capstone project that will include collecting, analyzing and developing insights from social media and/or digital marketing data in an industry and business of interest to them. Faculty will work to pair students with partner companies to supply data and business challenges to use as the foundation of the capstone project. Students will be required to deliver their analysis and communicate their results to their partner company sponsor as well as their faculty and peers.

Yes! Tell me more about Merrimack’s Business Analytics degree!


At Merrimack College, we’re proud of our long history of providing quality degrees to students entering the job market. Our faculty are more than just teachers. We are committed to helping you grow — academically, personally and spiritually — so that you may graduate as a confident, well-prepared citizen of the world.

Top 50 Best Value Online Big Data Programs 2018 by
Money magazine 2018 Most Transformative College
U.S. News & World Report 2020 #46 Best Regional Universities/North
U.S. News & World Report 2020 Top 10 Most Innovative School Regional Universities/North
The Princeton Review 2018 Best Regional College
Transitioning Athletics to Division 1 and joining the Northeast Conference in 2019-20