Certification:
Applied Business Analytics

The Certification in Applied Business Analytics is ideal for Amberton students who want to enhance their ability to successfully understand and initiate business analytics functions in modern organizations. Grounded in an array of analytics principles, the Applied Business Analytics Certification is a study of strategies, tools, methods, and applications that provide students with an understanding of the implementation of enterprise analytics to gain a competitive advantage. The four-course core curriculum focuses on contemporary business analytics theories and best practices. Students will acquire basic knowledge of business analytics tools, techniques, and processes necessary to effectively employ applications such as machine learning, artificial intelligence, linear/non-linear programming, optimization, and root cause analysis to support decision-making in modern organizations.

Certification Guide (PDF)

What Are the Requirements?

The Applied Business Analytics certification, focused on teaching and training adults in a corporate setting, requires 12 credit hours comprising specific courses, including:

• Data Analytics for Accountants

• Applied Business Analytics

• Operations Analytics

• Competitive Marketing Analytics

Students completing an Applied Business Analytics Certification will be able to:

• Analyze and apply the business analytics processes of acquiring, cleaning, combining, synthesizing, and analyzing large amounts of data from many sources.
• Effectively communicate business analytics insights, conclusions, and information clearly and concisely to support decision-making.
• Understand how to integrate and apply business analytics tools and techniques to disparate data within organizations to extract meaningful insights.
• Demonstrate knowledge of ethical issues and apply decision-making skills as they relate to the application of business analytics.
• Conduct relevant research appropriate to the understanding and application of business analytics.

Courses:  12 Hours

ACC6135 - Data Analytics for Accountants 

Students will develop a framework for using data analytics to increase efficiency, manage risk, and identify process improvements for their organizations and clients. Students will work through case studies related to financial accounting, managerial accounting, internal auditing, and auditing to expose them to the uses of descriptive, diagnostic, predictive, and prescriptive analytics.

MGT6460 - Applied Business Analytics

Students will become familiar with an overview and framework for understanding business analytics principles. Students will also be introduced to the theories, strategies, tools, and applied statistical techniques necessary to master the implementation of enterprise analytics to gain a competitive advantage. The course will focus on applying predictive analytics methods, processes, and best practices to common problems faced by organizations. Students will acquire knowledge of the tools, techniques, and processes needed to effectively employ enterprise analytics applications such as statistical modeling, machine learning, artificial intelligence, linear/non-linear programming, optimization, and root cause analysis.

MGT6470 - Operations Analytics

Students will be provided with an introduction to strategies that support the utilization of data to profitably match supply with demand through a given enterprise. In doing so, students will acquire competencies in the area of operations analytics through the review, application, and evaluation of the theories, strategies, tools, and methods that comprise the operations analytics body of knowledge. Course topics build on the origins, philosophy, and best practices of operations analytics to include analytical methods necessary to effectively employ enterprise applications such as analysis matrices, operation structures, artificial intelligence, key performance indicators, data analysis software, network diagramming, cost analysis, and targeting.

MKT6450 - Competitive Marketing Analytics

This course applies data analytics to problems in marketing to better understand customer needs and preferences; and to help organizations accomplish their strategic goals and objectives. Special emphasis will be placed on summarizing marketing data, forecasting new products, pricing strategies, estimating demand, market segmentation, calculating customer lifetime value, retailing, advertising, and internet and social marketing. Students will also learn how to construct models to support decisions in the areas of customer acquisition, engagement, satisfaction, and retention. This course will integrate the fundamentals of marketing analytics with research design best practices related to survey design, execution, and analysis; and qualitative methods including focus groups, case studies, and interviews.