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30 total credits required
Ohio University's online Master of Business Analytics (MBAn) features a curriculum grounded in the fundamentals of analytics. We frame our coursework to focus on business intelligence and how modern organizations use analytics to drive strategy. As a student, you will develop in-demand technical competencies while gaining a deep understanding of the data systems that power today's businesses and how those systems create value.
Because a previous technical background is not required, our comprehensive course progression is designed to help you build foundational knowledge early in your program, then gain additional skills through applied learning opportunities. For example, you will begin your program using software that may be familiar to you and progress to more sophisticated analytics tools (Tableau, Alteryx) and programming languages (SQL, R and Python) later.
In your final semester, you will partner with OHIO MBA students to solve a simulated business problem and apply many of the concepts learned throughout the program. You will also attend a required on-campus Leadership Development Conference to connect with fellow students, program faculty and OHIO alumni. This in-person event features guest speakers, panel discussions and workshops specific to MBAn students.
Data analysis is rapidly becoming a required skill set for today’s managers in competitive environments. As a decision-maker in business, you are likely to be asked to conduct your own analysis of data or to interpret a report that has been derived by others. In this course, you will have the opportunity to learn how to summarize, visualize, and manage data within software environments that are commonly used in business today. Additionally, techniques that help decision-makers reduce risk and identify opportunities that would provide an individual or a company with a competitive advantage will be reviewed.
Predictive analytics encompasses a variety of statistical and machine learning techniques and applications within a business environment. The primary goal of predictive analytics is to discover and apply relationships found within historic datasets to make predictions about the future or otherwise unknown events. In this hands-on course, students will be introduced to concepts related to constructing, testing, and applying quantitative models in various business settings. From this perspective, students will utilize major software tools to conduct an analysis of continuous, classification, and clustering models. Upon completion of this course, students will gain insight into how models are constructed and how predictive models can improve business.
Information systems have always been a critical component of the successful operation and management of organizations. Today, modern information systems are pervasive, and knowledge of how they integrate into businesses to enhance strategies and processes is essential for all positions and functional areas. Advances in digital technologies have resulted in the development of information systems that are radically transforming the nature of managerial work, the structure of organizations, and the way firms operate and compete in the marketplace. Managers must, therefore, have a solid understanding of information technology, its organizational role, and strategic implications. Regardless of your profession or position, you have little choice but to accept and assume responsibility for the innovative and effective use of information technology to enhance your organization's performance. This course is designed to provide the fundamentals necessary to begin this process.
This course provides a broad overview of business intelligence and data management including database fundamentals, business intelligence approaches, data management/data governance strategies, data mining, and other business/data analytics techniques. Our primary emphasis will be on the managerial perspective, focusing on how you can design, implement, and leverage business intelligence systems and strategies in a management role.
In this course, students will be introduced to programming concepts that are used in business analytics. Understanding the fundamentals of programming is an essential skill set to implement solutions that are commonly needed in business practices. Common scenarios include the automation of processing data sets, applying methods, and combining techniques for creating solutions to solve business problems.
Some refer to analytics as the new science of winning. It refers to a commitment by top management to the extensive use of data, statistical and quantitative analysis, explanatory and predictive models and fact-based management to drive decisions and actions. This course provides an introduction to analytics and covers spreadsheet modeling for decision-making. It employs techniques from the classical disciplines of statistics and operations research, as well as more recently developed methodologies: data mining, executive information systems, digital dashboards, and online analytical processing. You will be expected to master, at an introductory level, techniques that are at the heart of the competitive posture of many successful organizations.
Data is often either structured or unstructured. Unstructured data presents a challenge because standard techniques commonly used in business analytics cannot be used to discover meaningful patterns, relationships, and other insights that could be useful when solving business problems. In this course, students will learn advanced techniques while using software that is commonly used in practice to overcome the problems associated with unstructured data.
This course requires students to apply advanced software tools that are commonly used in businesses for advanced modeling practices and visualization techniques. In particular, students will explore advanced techniques for pre- and post-processing datasets. Students will apply advanced visualization techniques to understand the data that they are investigating and to enhance their ability to communicate the results and implications of predictive models. Students are expected to demonstrate the skills learned in this class with a course project. The course project not only allows a student to improve problem-solving skills, but it can also enhance the students’ ability to communicate their findings and recommendations in a business context.
This course will provide students with the opportunity to learn more about how business analytics is being used in a variety of workplaces. The course will have a strategic and managerial focus where students will analyze many business cases. These cases will challenge students in their ability to critically evaluate the implications of business analytics.
In this course, students will work in teams and apply course material to complete simulated business experience. In this simulation, the teams each run a fictitious firm. They will define a business problem to address, assess the organization and its context, suggest solutions, and deliver an action plan for implementing the solution. Teams compete with one another in a dynamic industry environment. This provides an opportunity to apply many of the concepts learned throughout the program.
The analytics practicum provides opportunities to apply techniques, applications, concepts, and models from prior coursework in the MBA program to support decision-making under uncertainty in a simulated competitive business environment. Data that is generated from each student’s work during the concurrent MBA 6912: Applied Business Experience course will be used to complete a set of sequential assignments. Students will have the option of using results of each assignment for decision-making in the MBA 6912 course. Upon completion of the two courses, students will have been exposed to the outcomes of their strategic and tactical approaches to managing a type of manufacturing business.
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