- BSA 2050 Introduction to Programming
- BSA 2100 Managing Business Systems
- BSA 3110: Cybersecurity Fundamentals
- BSA 3220: Computer and Network Security
- BSA 3300 Business Systems Analysis
- BSA 3620 Database Modeling, Design and Analysis
- BSA 3860 Data Security, Governance and Ethics
- BSA 3950, 4950 Studies Abroad
- BSA 4010 NoSQL Database Applications
- BSA 4250 Predictive Analytics
- BSA 4330: Ethical Hacking and Penetration Testing
- BSA 4440: Management and Communication of Information Security
- BSA 4350 Data Analytics and Visualization
- BSA 4450 Special Topics in Business Systems and Analytics
- BSA 4510 Supply Chain Analytics
- BSA 4530 Analytics for Enterprise Systems
- BSA 4550 Enterprise Systems
- BSA 4650 Big Data Analytics
- BSA 4730 Project Management
- BSA 4750 Business Analytics Practicum
This course is designed as an introduction to programming and the programming language Python, for the student who has little to no programming knowledge and experience. The course can be used as preparation for more advanced programming courses, as well as a self-contained course for students who want to use Python for their studies or professional work. Python is an interpretive language with a simple syntax. While it is easy for beginners to learn, it is widely used in many disciplines for data exploration and analysis. This course will use various methods of instruction including labs, group projects, and in-class discussion.
This course offers an overview of the manner in which information systems support business processes, managerial decision-making, and organizational strategy. Additionally, students will develop technical skills using productivity software like Excel to process and analyze data to support managerial decision making.
This course is designed to teach students the roles and responsibilities of the business analyst, the structured process for analyzing a business and its systems, and how to determine a business system's viability.
This course provides students with skills that will facilitate the effective use of database management systems. Key components of this course include relational data modeling along with database design, development and implementation. Students will query and analyze data using SQL.
This course provides an overview of data security, governance and ethics as it applies to government, corporate and individual data. Both technical aspects of data security and policy level issues around data privacy are covered from a corporate perspective. Students learn the current regulatory system affecting different types of personal data and methods of data anonymization that protect privacy while keeping data usable for corporate consumption. Data ethics is covered in terms of privacy, data manipulation, data sharing and ownership, conflict of interest, and communications.
Study in a foreign country. Individual course titles and locations are assigned for each course taken. See Studies Abroad program for details.
This course explores nonrelational databases commonly referred to as NoSQL databases and the characteristics that distinguish them from relational database management systems. Core concepts of NoSQL databases will be presented along with criteria that decision makers should consider when choosing between relational and nonrelational databases.
This course provides students a practical, hands-on learning environment focusing on data mining and predictive analytics to solve business problems. Students will prepare data, create and validate predictive models, and deploy those models to predict future events and uncover hidden patterns of behavior. Students will examine how data analysis technologies can be used to improve decision-making by studying the fundamental principles and techniques of data mining to develop data-analytic thinking.
This course teaches students how to work with different types of data and utilize analytical tools to solve business problems. Students will identify data requirements, utilize statistical techniques to evaluate data quality and completeness, prepare data for analysis, and transform data into useful information. Students use tools like Alteryx, Tableau and SQL Server for data prep and analysis. Students learn how to effectively communicate their analytical insights through a combination of in-class activities, software demonstrations, and individual and team projects.
This course offers the student an opportunity to explore and study a special current business systems and analytics topic not covered in other information systems management courses.
This course introduces students to the principal analytical tools and methods used in supply chain management. The course provides analytical tools and helps develop analytical skills needed to solve relevant supply chain and logistics problems. These problems include but are not limited to supply chain cost minimization, network optimization, pricing and procurement decisions, outsourcing decisions, and sales and operations planning.
This course provides a hands-on approach to conducting business analytics with enterprise systems. Enterprise systems like SAP contain the overwhelming majority of the world’s business transactional data. Students will develop an understanding of enterprise data structures and how to use them for reporting, visualization and prediction. This course uses various methods of instruction including labs, group projects and in-class discussion.
This course will examine enterprise systems. Enterprise systems are a class of information systems that encompass multiple business areas within an organization. They include enterprise resource planning (ERP) systems; customer relationship management (CRM) systems; supply chain management (SCM) systems; knowledge management (KM) systems; and others. Students will learn how businesses use these systems in order to make daily operational decisions as well as long-term, strategic decisions. In the latter part of the course, students will engage in a business simulation using an ERP system to process transactions and make decisions about purchasing, pricing and production.
This course introduces students to the fundamental technologies, platforms, and methods that enable Big Data analysis. Students learn how to process Big Data on platforms that can handle the volume, velocity, variety and veracity of Big Data. Students learn how to setup and operate Big Data platforms to complete real world, Big Data analysis tasks that allow them to become comfortable with summarizing and communicating their findings.
Students learn the fundamentals and best practices of project management methodology as it applies to IT initiatives. Students examine all aspects of IT projects, including hardware, software, vendor relationships, and stakeholder communication. Students walk through a complete project management life cycle, including initiating, planning, executing, controlling, and closing.
This capstone course demonstrates how business analytics is strategically used by organizations to gain a competitive advantage in today’s data-driven environment. This course introduces students to various business analytics applications, cases and software tools to help understand, interpret, and visualize business data. This project-based course will partner student teams with industry professionals to work on guided projects illustrating various aspects of descriptive, diagnostic, predictive and prescriptive analytics using a variety of statistical applications to develop data-driven insights leading to intelligent solutions.