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Darla Moore School of Business


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Certificate Programs

Graduate students can enhance their degree program with graduate certificates that align with their interests and career goals. Graduate certificates are noted in the graduate’s transcript, and graduates received a separate diploma awarding a “Post-Bachelor Certificate” in the specific area of knowledge.

Graduate Certificate in Business Analytics

The Business Analytics Graduate Certificate is designed, based on extensive benchmarking across academia and industry, to train the data-savvy managers that today’s marketplace demands.

 

Academic Requirements

Despite staggering increases in the ability to capture and store data, the majority of business decisions continue to be made in the same ad hoc fashion as they were before the information age. One of the reasons we do not see more data-driven decision-making is that companies have an abundance of data but lack the ability to turn the data into useful knowledge. To accomplish this, firms need managers and leaders who combine solid business and communication skills with an analytics skillset. A recent study by the McKinsey Global Institute found that U.S. businesses looking to capitalize on the massive volumes of data available today face a shortage of 1.5 million of these types of managers who are well-trained in data analytics.

Candidates pursuing this certificate are required to complete four courses (12 credit hours) beyond the MBA core course work; three of them required and one that may be chosen from a list of provided electives.

 

Graduate Certificate in Business Analytics

Required Courses:

  • MGSC 777 — Advanced Quantitative Methods
  • MGSC 891 — Data Resource Management
  • MKTG 708 — CRM/Data Mining

Additional Courses: (one required)

  • CSCE 587 — Big Data Analytics
  • FINA 772 — Portfolio Management
  • MGSC 778 — Revenue Management
  • MGSC 796 — Information Systems
  • MKTG 717 — Marketing Spreadsheet Modeling

Course Descriptions

*MGSC 777 — Advanced Quantitative Methods in Business
Students will gain experience using cutting-edge analytical tools to support business decision-making, including advanced topics in data visualization, geographic information systems and Excel development with VBA. In addition, this course has a focus on written and verbal communication of analytical results.

*MGSC 891 — Data Resource Management
This course is an overview of data resource management, including database technology and design, information architecture planning, and database administration. A design project is required.

*MKTG 708 — CRM/Data Mining
Firms have invested considerable resources in setting up customer relationship management (CRM) programs, while improvements in technology and software have provided the means to analyze key outcomes of CRM programs (as measured by satisfaction, loyalty and profitability). Implementing a CRM marketing program entails extracting meaningful information from large databases using analytical techniques (commonly referred to as data mining), developing insights and strategies, and then implementing them. The topics that will be covered in this course include basics of customer relationship management, customer lifetime valuation analysis using transactional data and data mining using Excel Miner to perform hands-on analytics. Students will develop skills related to multiple linear regression, classification and regression trees, logistic regression, neural networks, discriminant analysis, market basket analysis and cluster analysis. Companies use these techniques to evaluate customer profitability, target profitable customers and implement data-driven marketing decisions.

CSCE 587 — Big Data Analytics
This course covers foundational techniques and tools required for data science and big data analytics. The course focuses on concepts, principles and techniques applicable to any technology environment and industry. Tools such as R and MapReduce/Hadoop are covered. (Note that this is a full-semester course in the Department of Computer Science.)

FINA 772 — Portfolio Management
Utilizes the techniques learned in FINA 762 to analyze and recommend investment opportunities for a portion of the Moore School endowment. The course culminates with a sequence of presentations and recommendations to the Moore School’s Business Partnership Executive Board.

MGSC 778 — Revenue Management
This course covers the concepts of forecasting demand, segmenting customers, and allocating capacity or customizing price offers to each distinct customer segment such that the firm's profits are maximized.

MKTG 717 — Marketing Spreadsheet Modeling
This course focuses on the conceptual foundations and application of basic econometric and statistical models used in marketing analytics contexts. The understanding of such models should enable students to properly use them in real business settings using commonly available software. 

*Required course for Business Analytics functional specialization.

Graduate Certificate in Enterprise Resource Management

Along with the general trend in business toward massive automation, large scale enterprise resource planning (ERP) systems have become the backbone of today’s information systems. These systems integrate information from all areas of an organization (i.e., marketing, operations, HR, sales) as well as up and down the supply chain.

 

Academic Requirements

Increasingly, business managers must demonstrate proficiency in their understanding of ERP systems and be able to design, employ and use these systems effectively as a requirement to a successful career. The Graduate Certificate in Enterprise Resource Planning is designed to provide students with the ability to demonstrate an overall understanding and working knowledge of the function, design, control and use of ERP systems. It is based on the premise that students should understand at a conceptual level both their own technology as well as the technology of the entities with which they interact. In addition to understanding ERP systems, this certificate also focuses on understanding how, administratively and operationally, each area of the organization interacts, leverages and affects the others to create a desired outcome across the organization. The curriculum provides students with sufficient conceptual understanding and applied skills to be able to navigate the complexities of transaction processing and data queries inherent in modern ERP systems. Emphasis is given to the predominant ERP system within large organizations, which is SAP, culminating in SAP TERP 10 instruction and the TERP 10 examination. Candidates pursuing this graduate certificate are required to complete three courses (nine credit hours) beyond the International MBA core coursework — two of them required and one that may be chosen from a list of provided electives.

 

Graduate Certificate in Enterprise Resource Planning

Required Courses:

  • ACCT 737 — Accounting Information Systems from a Strategic Perspective
  • ACCT 739 — Enterprise Resource Planning

Additional Courses: (one required)

  • ACCT 702 — Application of Advanced Databases to Accounting and Business
  • MGSC 891 — Data Resource Management

 

Course Descriptions:

*ACCT 737 — Accounting Information Systems from a Strategic Perspective
Design and implementation of accounting information systems to achieve strategic objective.

*ACCT 739 — Enterprise Resource Planning Systems
Business process integration within enterprise resource planning systems including the use and management of the enterprise core modules within ERP software implemented companies.

ACCT 702 — Application of Advanced Databases to Accounting and Business
The integration, configuration and operation of accounting information within enterprise resource planning and other databases as applied to current business practices.

MGSC 891 — Data Resource Management
Overview of data resource management, including database technology and design, information architecture planning, and database administration. A design project is required.

*Required course for Business Analytics functional specialization.