Haub School of Business

Department of Decision & System Sciences

Curriculum
Objective

The BUSINESS INTELLIGENCE (BI) major focuses on learning how analytics and technology can be used to enhance organizational sense making, decision-making, and performance. Business Intelligence refers to the skills, technologies, applications, and practices used to help a business acquire a better understanding of its commercial context. BI applications provide historical, current, and predictive views of business operations. BI applications commonly utilized by businesses are OLAP, data mining, business performance management, performance benchmarking, text mining, predictive analytics, and fraud detection.  The Business Intelligence major is therefore designed to equip the 21st century manager or analyst with the relevant skills to succeed in a technology-driven, data-intensive world. Majors acquire general business skills plus knowledge and experience in programming, systems theory, systems analysis & design, process analysis, database management, decision support systems, database querying and reporting, online analytical processing (OLAP), data mining, statistical analysis, quantitative analysis, forecasting, project management, competitive intelligence, knowledge management, and supply chain and CRM activities. Technology employed in the DSS curriculum includes Microsoft Office, Oracle, SPSS Clementine, and Visual Basic. Students may also have exposure to SAP, Microsoft SharePoint, Crystal Ball, and other important technologies.

The BUSINESS INTELLIGENCE (BI) MINOR is designed to enhance the skill set of both Business and Arts & Sciences majors so that they are fundamentally better equipped to succeed in a data-intensive world. Organizations typically gather information in order to assess their operating environment, to conduct marketing research, to manage customer relationships, and to perform competitive analyses or security assessments. Businesses employ BI techniques in an attempt to gain sustainable competitive advantage, and regard such intelligence as a valuable core competence. Non-profit organizations and government, including such entities as Homeland Security and the military, also use BI techniques to discover opportunities for improving their operations.

Requirements for the Business Intelligence Major 

GER Common Courses (See Curricula): six courses

GER University Distribution (See Curricula): fourteen courses, including

Mathematics—one of the following two-course sequences:

MAT 1151 Finite Mathematics with Applications in Business

MAT 1161 Brief Business Calculus

or MAT 1251-1261 Calculus for Biology and Social Science

or MAT 1351-1361 Calculus I-II

Social/Behavioral Science:

ECN 1011 Introductory Economics (Micro)

ECN 1021 Introductory Economics (Macro)

GER Electives: any three courses

Business Foundation: ten courses, including

ACC 1011 Concepts of Financial Accounting

ACC 1021 Managerial Accounting

MGT 1001 Legal Environment of Business

DSS 1311 Business Statistics

FIN 1341 Introduction to Finance

MGT 1011 Organizations in Perspective

MKT 1011 Principles of Marketing

DSS 1011 Introduction to Information Systems

DSS 2011 Quantitative Methods for Business

BUS 2901 Business Policy

Major Concentration: six courses

Required Core

DSS 2111 Systems Theory

DSS 2311 Database Management

DSS 2411 Systems Analysis and Design

DSS 2711 Decision Support System Modeling

DSS 2721 Advanced Decision-Making Tools

Plus one of the following courses

DSS 2511 Communication Technologies & Enterprise Security

ACC 2131 Management Accounting Information Systems II

DSS 5015 Six Sigma Applications and Foundations I

DSS 5035 Six Sigma Applications and Foundations II

Other Courses

DSS 2911 Independent Study I Majors only & permission of the Chair

DSS 2912 Independent Study II Majors only & permission of the Chair

DSS 2953 Honors Research I Majors only & permission of the Chair

DSS 2963 Honors Research II Majors only & permission of the Chair

DSS 2981 Internship I Majors only & permission of the Chair

DSS 2991 Internship II Majors only & permission of the Chair

Requirements for the Business Intelligence Minor

Required Core

DSS 1311 Business Statistics

DSS 2011 Quantitative Methods for Business

DSS 2311 Database Management

DSS 2711 Decision Support System Modeling

DSS 2721 Advanced Decision-Making Tools

Plus one of the following courses

DSS 2111 Systems Theory

DSS 2511 Communication Technologies & Enterprise Security

ACC 2131 Management Accounting Information Systems II

DSS 5015 Six Sigma Applications and Foundations I

DSS 5035 Six Sigma Applications and Foundations II

 

DSS     1011     Introduction to Information Systems     3 credits

This course explores the impact of information technology to ascertain how technology enables business operations, decision-making, and performance. Students are also required to take online Microsoft Excel tutorials and to pass an Excel competency requirement as part of this course.

DSS     1013     Introduction to Information Systems: The Road to RIO     3 credits

This version of “Introduction to Information Systems” is intended for Honors students (See Honors Department Listing for HON -1713) and for interested Information Systems majors. This course explores the fundamentals of information technology from more than one viewpoint. We explore many of the historical, social, cultural and ethical issues connected with information technology as well as the core technology concepts. Students will gain basic fluency in the information technology tools and examine one of the issues above in depth

DSS     1311     Business Statistics     3 credits

This course covers probability concepts as well as descriptive and inferential statistics. The emphasis is on practical skills for a business environment. Topics include probability distributions, estimation, one-sample and two-sample hypothesis testing, inferences about population variances, and chi-square test of independence. Students will also become familiar with spreadsheet applications related to statistics and with statistical software. Prerequisite: DSS 1011, MAT 1151-1161.

HON (DSS) 1723 Business Statistics - Honors: Candles in the Dark-Illuminating Data 3 credits

This version of “Business Statistics” is intended for Honors students. This course is intended for students who wish to have an enriched experience in Business Statistics. The goal is for each student to develop a high level of competency in solving practical problems in the business world and to lay a firm quantitative foundation for future study. Topics include: descriptive statistics, probability, discrete and continuous random variables, sampling distributions, confidence intervals, and hypothesis testing. Heavy emphasis is placed on casework and team projects. Content is covered on a “need to know” format. Prerequisites: DSS 1011, MAT 1151-1161 or MAT 1351-1361 Satisfies DSS 1311 for Business majors or minors

DSS     2011     Quantitative Methods for Business     3 credits

Every organization, must manage a variety of processes. In this course the student will development an understanding of how to evaluate a business process. Additionally, the art of modeling, the process of structuring and analyzing problems so as to develop a rational course of action, will be discussed. The course integrates advanced topics in business statistics—linear and multiple regression and forecasting, production and operations management—linear programming and simulation, and project management. Excel software is used for problem solving. Prerequisite: DSS 1311.

HON (DSS) 2723 Quantitative Methods for Business: Modeling Tools for Thinking 3 credits

This course is intended for students who wish to have an enriched experience in Quantitative Methods for Business. In this course the student will development an understanding of how to evaluate a business process. Additionally, the art of modeling, the process of structuring and analyzing problems so as to develop a rational course of action, will be discussed. The course integrates advanced topics in business statistics—two sample hypothesis testing, linear and multiple regression and forecasting, production and operations management—linear programming and simulation, and project management. Prerequisite: DSS 1311 or equivalent. Satisfies DSS 2011 for Business majors or minors.

Business Intelligence

DSS     2111     Systems Theory     3 credits

Change, as it occurs within a “system,” is a topic that needs elucidation from a perspective, which has attained theoretical respectability within the social sciences. The teaching of System Analysis and Design gives “lip-service” to system while de facto spends the entire course teaching the methodologies, tools, and techniques needed to perform analysis and then design. This course treats the concept of “system” in its fullness and then uses case studies to document both failure and success of technology-oriented companies through the treatment of the company as a system.

DSS     2311     Database Management     3 credits

The course provides an in-depth understanding of the database environment. Besides covering the important process of database design, this course comprehensively covers the important aspects of relational modeling including SQL and QBE. Students will be required to design and develop a database application using a modern fourth generation language system. Prerequisite: DSS 1011

DSS     2411     Systems Analysis and Design     3 credits

This course will introduce the student to structured project management concepts, techniques, and applications through exploration of the Systems Development Life Cycle (SDLC). Lectures, in-class discussions, and real-life examples will be used to build a toolkit of project management, technology evaluation, and post-mortem critique skills. These skills will prove extremely valuable to students in a professional Systems Analyst role upon graduation. Prerequisite: DSS 1011.

DSS     2511     Communication Technologies & Enterprise Security     3 credits

This course examines the new realities of telecommunications, reflecting today’s most critical issues, trends, and technologies. In addition, since a wired world has major consequences for organizations, the course examines security concerns that require firms to develop strategies to protect data and its communication. Prerequisite: DSS 1011.

DSS     2711     Decision Support System Modeling     3 credits

We will build a basic understanding of supply chain issues and learn to model some of the problems encountered in supply chain management. This course will introduce methods for creating user-friendly applications and models in Excel by taking advantage of the powerful macro language for Microsoft Office, Visual Basic for Applications (VBA). The skills to analyze and present the results in a non-technical matter will be developed through a series of practical exercises. Prerequisites: DSS 2011 and 2311.

DSS     2721     Advanced Decision-Making Tools     3 credits

This course focuses on the application of decision-making tools used to develop relationships in large quantities of data for more than two-variables. Comprehension of when to use, how to apply, and how to evaluate each methodology will be developed. This course will additionally provide an introduction to data mining tools. Data Mining consists of several analytical tools, such as neural networks, decision trees, evolutionary programming, genetic algorithms, and decision trees, used to extract knowledge hidden in large volumes of data. An understanding of how these data mining tools function will be developed so as to provide insight into how to apply these tools. Statistical and data mining software will be used. Prerequisites: DSS 2011 and 2311.

DSS     5015     Six Sigma Applications and Foundations I     3 credits

This course is the first of a two course sequence that prepares the student for the Six Sigma Green Belt certification examination. Topics include introduction of Six Sigma and its vocabulary, review of business statistics focusing on hypothesis testing and multiple regression, experimental design and Analysis of Variance, statistical process control, analytic hierarchy process, discrete event simulation and other tools of Six Sigma. This course includes roughly half of the material covered on the Green Belt certification exam.

DSS     5035     Six Sigma Applications and Foundations II     3 credits

This course is the second of a two course sequence that prepares the student for the Six Sigma Green Belt certification examination. Topics include the Six Sigma dashboard and related models (DMAIC, DMADV, DFSS: QFD, DFMEA, and PFMEA), selecting and managing projects, organizational goals, lean concepts, process management and capability, and team dynamics and performance. This course includes the remaining material covered on the Six Sigma Green Belt certification exam. Students may take this course without having taken DSS 5015.