B2B – LP MAHIMA 2018-10-24T09:46:41+00:00

Special Offer for MaHIMA members!

Pursue Your Online Master’s Degree in
Data Science or Business Analytics

Merrimack College is Proud to Partner with MaHIMA

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tuition discount per credit hour for MaHIMA members

Yes! Tell me more about master’s degrees at Merrimack!

MaHIMA has partnered with Merrimack College to provide a tuition discount for these exciting Master of Science programs.  Members of the Massachusetts Health Information Management Association will receive a discount of $50 off per credit hour, a savings of $1,600.


Learn to harness the power of both unstructured and structured data using the latest tools and analytical methods. Curriculum covers data management & engineering in depth, as well as advanced statistical modeling, algorithms, and machine learning.


Generate business insights from complex data sets to guide organizations toward informed & actionable decisions. Covers a range of statistical models, providing the flexibility to tackle both tactical and strategic issues with many different data types.

What Skills Will You Develop?

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 has 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 statistical 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 interdepence 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.

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MaHIMA is Committed to Developing Tomorrow’s Data Scientists and Business Analysts

The Business Analytics and Data Science Degrees from Merrimack are:

  • 100% Online

  • Employer aligned

  • Taught by leading practitioners

  • Easy application process!


“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

Discover the Merrimack Difference


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.

  • Money magazine 2018 Most Transformative College
  • US News & World Report 2018 #50 Best Regional Universities/North
  • US News & World Report 2018 #11 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

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