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Business Analytics

Bachelor of Science Degree

Gain the knowledge you need to be the go-to-person in the job market today. The curriculum for includes business strategies, microeconomics, financial accounting, statistical and quantitative methods, plus an introduction to programming, information systems, applied statistics, data management, data mining, and business intelligence - in short, what you need to know to analyze the applications of business analytics in real-world business situations, evaluate database systems to support business analytics applications, and apply the primary statistical, quantitative and business analytics tools and techniques to support common business decision-making applications.

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Courses in the major include:

This course is an introduction to accounting concepts and the elements of financial statements including basic accounting vocabulary and analysis of business transactions from an accounting viewpoint. Students will be required to recognize, record, and classify new accounting data. Emphasis is placed on corporate accounting. Introductory financial statement analysis and interpretation are also covered. Prerequisite: none
Managerial accounting is designed to introduce the fundamentals of managerial accounting to both accounting and non-accounting majors. It covers accounting and management decision making in both short-term and long-term strategic situations. Students will be expected to explain and apply accounting concepts including basic costing and processes, cost classifications, responsibility accounting and ethical behavior of the managerial accountant. Prerequisite: AC 205
This course provides a comprehensive introduction to the field of marketing. It covers the current marketing concepts and practical applications that will include the functions of product, price, place, promotion, and positioning. Additional emphasis will be given to multicultural and global marketing in the United States and internationally.
This course covers the basic principles, techniques, and institutional aspects of financial management in order to provide students applications of finance content similar to those encountered in a finance career. Topics include financial markets and environment, time value of money, bond and stock valuation, risk and return, financial statement ratio analysis, capital budgeting, financial planning and control, capital structure, dividend policy, and other fundamental finance issues. Prerequisites: AC 206, BAN 200 or MA 215, and MA 102
This course introduces quantitative models appropriate for business applications. Emphasis is on analytical thinking, applied business decision-making, and practical real-life problem solving. The course starts with an introduction to models and mathematical model building. Specific models and applications include: linear programming and its transportation, transshipment, and assignment topics; project management; deterministic models of inventory control; queuing theory and economic analysis of waiting lines; and forecasting with emphasis on time-series and causal models. Software will be applied, as appropriate, in solving large-scale problems. Prerequisites: MA 102 or MA 120 and MA 215
This course is designed as the entry point to learning SAS programming language and analytics programming concepts to gain business intelligence. It provides the tools necessary to write SAS programs to perform data management, analysis, and reporting including the creation of simple reports and computing basic statistics on data set variables. Hands-on exercises designed to facilitate understanding of business systems and business processes are included. The course also provides the basis for more advanced work in business analytics and advanced programming techniques for data modeling. This course aligns with the SAS Base Programming certification concepts.
This course offers an in-depth exploration of all the major topics in the field of data and information management from an applied perspective. The course is designed to provide not only a strong theoretical foundation, but also the technical skills required in analyzing, designing, implementing, managing, and utilizing information repositories. Topics covered include relational database model, data modeling, logical and physical database design, structured query language (SQL) implementation, procedures and triggers, data integration and quality, data warehouses and database administration. This course explores data and information management related issues in the context of business organizations; therefore, strategic roles that data and information play in business operations, customer relationship management, business decision-making, and strategy development are also discussed.
This course introduces an analytical toolset to address business problems. The course provides an overview of the key concepts, applications, processes and techniques relevant to data modeling for business intelligence. The course makes use of SAS Enterprise Miner to illustrate the use of business analytics methodologies to enhance decision-making.
This course provides an in-depth discussion on the data warehousing, data mining, analytics used for business intelligence. A variety of data analysis tools will be used to discover patterns and relationships in data that may be used to make proactive, knowledge-driven decisions. The course provides an in-depth discussion on various techniques of data mining including data modeling, pattern recognition, predictive analytics, and text mining. Prerequisite: BAN 400
This course is designed to introduce the concepts of structured programming. How programs and programming languages work, and the purposes and practices of structured programming are discussed. Designing, coding, documenting, and debugging programs using elementary data structures, input/output statements, selection and iteration, functions, and one-dimensional arrays are covered in detail.
A project-based course which focuses on the use of tools and methodologies applied to structured system analysis and design. Emphasis is placed on traditional approaches including enterprise analysis, workflow analysis, data flow analysis, affinity diagram construction and use, system flowcharting and entity relationship diagramming. Students will complete a feasibility analysis, risk analysis, design specifications and a project implementation plan for a simulated business system.
This course will explore the fundamental technical principles of telecommunications and computer networks with an examination of the business challenges of managing communications resources.
This course focuses on the strategic role of information technology and information systems in today's business environment. Topics will include challenges faced by managers of business firms, understanding the technologies that will help managers meet these challenges, designing business processes to take advantage of the technologies, and creating management procedures and policies to protect the firm's assets. This course provides the IT professional with an understanding of the dynamic, increasingly globalized and technology intensive business environment.
This course provides an introduction to the area of Microeconomics. This introduction assists students in achieving a practical understanding and ability to apply economic concepts, theories, and practices relevant to the understanding of our economy. The course investigates the economic behavior of consumers, businesses and government. Emphasis is placed on price and output determination under various market structures and on the entrepreneurial competitive process. Prerequisites: Basic college level ability in English, logic, and mathematics
This course provides the theoretical basis and problem-solving experience needed to apply the techniques of descriptive and inferential statistics, to analyze quantitative data, and to improve decision making over a wide range of areas. Topics covered include descriptive statistics, linear regression, data gathering methodologies and probability, as well as confidence intervals and hypothesis testing for one and two samples. Use of technology in solving and interpreting statistical problems is emphasized. Prerequisite: MA 101 or placement via ALEKS Placement Assessment

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