Master of Science in Business Data Analytics (MSBDA) Course Descriptions

BISI 6130: Management and Evaluation of Information Systems

This is a survey course of information technology (IT), and its impact and role in the business environment. Issues concerning the strategic, tactical, and operational uses of IT and information systems are examined. The challenges and the methods of managing IT are presented using the socio-technical approach. Types of information systems and their application within organizations are discussed through case studies.

BDAS 6140: Fundamentals of Business Data Analytics

The course provides students with an overview of how analytics is used in various business disciplines. Students develop critical skills for today's intensive, data-driven decision making through practical-use cases cutting across multiple business functions.  Students will learn and gain experience with relevant software tools and apply the latest techniques in data management, exploratory data analysis and visualization, design of experiments, descriptive analysis, predictive analysis, and data mining to data describing markets, customers, products, services, and industries.

BDAS 6150: Database Management Systems

The course provides students with advanced concepts in data management and in the strategic use of data. Topics include data strategy, business intelligence, big data, data mining and the strategic use of data warehouses, data quality, the business value of data, unstructured data, modern data administration, master data management, data management in cloud computing, data issues in agile development, and other contemporary data topics.  The course also covers data modeling and structure, and database query languages (SQL, NoSQL, and NewSQL).

BDAS 6210: Business Intelligence

The course focuses on computerized support for management decision making. Topics include artificial intelligence, machine learning, intelligent agents, etc. The course will discuss business use cases, personalization (targeted ads) and recommendations, fraud detection, smart cars, chat bots, future of AI, and how AI will impact jobs and companies.  The role of information technology in strategic decision making and in business intelligence analytics will be studied.

BDAS 6220: Data Visualization

The course will cover data acquisition, cleaning, analysis, and visualization. This course exposes students to readily available and state-of-the-art tools to discover trends and make informed business decisions in fields such as finance, information sciences, marketing, healthcare, risk management, and others.  This course will provide an overview of techniques for effectively translating and communicating quantitative and qualitative data into readable graphics to varied audiences, including decision makers in public and private organizations.  Visualization and communication tools such as promotional materials (e.g., infographics), statistical graphs and plots, and effective oral and written communications will be covered.

BISI 6250 Decision Support Systems

The key technical and managerial issues in the development and use of decision support systems (DSS) in organizations are addressed. The strategic management decision making process and the role of DSS in the process are explored. Contemporary topics including Expert Systems, Executive Information Systems, Data warehousing, data visualization, and Group Decision Support Systems are reviewed. Research effort is on the real-life use of these technologies in specific business areas.

BDAS 6260: Data and Text Mining

Student will acquire knowledge in pattern discovery and recognition in sets of data using data analytics tools.  The course covers topics including data (structured, unstructured, and big data) collection, extraction, cleaning/preparation, transformation, applying data mining models on the data, and evaluation of the models. Hands-on skills will be employed using data analytics tools such as Tableau, Rapid Miner, IBM Modeler, Microsoft SQL, and R.

BDAS 6270: Big Data Analytics for Business

This course provides students an excellent exposure to the world of Big Data.  Students will gain general knowledge of analytic techniques such as statistics, data mining, visualization of data, and basic machine learning. Upon completion of this course, students will be able to understand the sources, collection, management, analysis, and presentation of large volumes of structured and unstructured data in an effective and efficient manner. Students will be exposed to modern information technology tools to enhance data analytics and visualization. 

BISI 6550 - Project Management

This course explores the techniques to successfully manage business projects. The topics covered include scope, time, cost, quality, human resource, communications, risk, integration and procurement management. The processes covered include initiating, planning, executing, controlling, and closing of projects. Students will have the opportunity to use current project management software.

BDAS 6280 Predictive Data Analytics

This course helps students develop skills in predictive modeling and analytics to improve organizational performance. The students learn how to identify situations where predictive analytics could be used. They also learn tools and acquire skills for data definition, extraction, transformation, analytical modeling, and exploiting patterns found in historical and transactional data for identifying risks and opportunities. This course focuses more on tools and applications than on the theoretical basis of predictive analytics.

BDAS 6410: Healthcare Analytics

This course explores the purpose and value of healthcare data analytics. Students will study data analytical processes that enable decision making in healthcare. Topics will include database management and querying, data visualization, data capture tools, data mining, data warehouses, and decision support with healthcare data. Students will analyze healthcare information and data to identify trends of quality, safety, and effectiveness of healthcare. The concepts learned in this course will assist the student in identifying opportunities in which health analytics can be used to improve performance and support important decisions for healthcare enterprises.

BDAS 6420: Marketing Analytics

This course focuses on how to design experiments, collect, analyze data report result, in order to expand marketing theory and practice, competitive intelligence gathering, customer segment analysis, integrated marketing technologies, customer relationship management. Topics include advanced data mining and machine learning with applications in areas such as acquisition modeling, up-sell modeling, cross-sell modeling, churn modeling, and customer lifetime modeling.  Topics will also include analytical methods such as regression, decision trees, neural networks, random forests, advanced performance measures, and bias-variance tradeoffs.

BDAS 6470: Special Topics in Business Data Analytics

The course investigates and presents specialized business data analytics topics of importance to industry.  Students are presented real-world data to gain experience. The topics are selected based on the current trends in the field. The syllabus will be developed based on the special topic selected for the course to offer in a specific semester.

BDAS 6610: Data Analytics Capstone
The Capstone course is designed to give students a chance to apply the algorithms, methods, and tools they've learned in the program to solve real-world data analysis problems with interdisciplinary characteristics. Students will collaborate on a team project that covers key aspects of the data analytics process, culminating in a consolidated report and a final presentation. This course serves as a capstone experience, preparing students for their careers by providing hands-on experience in teamwork, project planning, report writing, presentation skills, and professional results interpretation.

BDAS 6560: Soft Skills for Data Analysts
Soft Skills for Data Analysts is a comprehensive course designed to equip students with the essential non-technical skills necessary for success in the field of data analysis. The course focuses on developing communication, teamwork, problem-solving, and critical thinking skills, all of which are crucial for effective data analysis in a professional setting. Through a combination of lectures, case studies, and practical exercises, students will learn how to effectively communicate complex data analysis results to non-technical stakeholders, collaborate with team members from diverse backgrounds, and navigate the ethical and social implications of data analysis.