Helzberg School M.S.-BIA Curriculum
The M.S. in business intelligence and analytics curriculum consists of 26 core credit hours, four credit hours of electives of your choice, and any prerequisite courses needed.
Classes meet once per week from 5:45 to 9 p.m., Monday through Thursday. Most students attend class two evenings per week. See course descriptions below.
- Business Intelligence, BIA 6300 (2 credit hours)
- Data Visualization, BIA 6302 (2 credit hours)
- Applied Data Mining, BIA 6301 (2 credit hours)
- Predictive Models, BIA 6303 (2 credit hours)
- Text Mining, BIA 6304 (2 credit hours)
- Web and Social Media Analytics, BIA 6306 (2 credit hours)
- Big Data and Prep, BIA 6305 (2 credit hours)
- Strategy and Analytics, BIA 6308 (2 credit hours)
- Dashboard Creation and Implementation, BIA 6307 (2 credit hours)
- Managerial Communications, MG 6008 (2 credit hours)
- Financial Decision Making for Managers, ACFN 6300 (2 credit hours)
- Project Management, MG 6320 (2 credit hours)
- Marketing, MK 6410 (2 credit hours) or MK 6460 Marketing Research and Analysis (2 credit hours)
Core courses already taken through another degree program can be substituted with an additional elective. Program director consent is required.
BIA 6300. Business Intelligence (2 credit hours)
Business leaders must have the ability to collect and interpret information concerning customers, suppliers, and competitors, and make decisions that affect their company's performance. Business intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information to enable more effective strategic, tactical, and operational insights and decision-making with an emphasis on knowledge management. Using the case study approach in combination with contemporary software tools, students will apply the concepts of business process analysis, quality control and improvement, performance monitoring through performance dashboards and balanced scorecards, and process simulation.
BIA 6302. Data Visualization (2 credit hours)
This course is about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software. Students will be able to present complex quantitative and qualitative data visually. Participants will learn to explore a range of different data types and structures. They will learn about various interactive techniques for manipulating and examining the data and producing effective visualizations. Participants will be guided through an exploration of quantitative business data to discern meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities. Data visualization is both an art and a science. It is an art concerned with unleashing creativity and innovation, designing communications that appeal on an aesthetic level and survive in the mind on an emotional one. Statistics and exposure to any programming language is required. The primary software tool for this class will be Tableau. R and Python1 will also be incorporated. Prerequisite BIA 6300.
BIA 6301. Applied Data Mining (2 credit hours)
The course provides a comprehensive overview of data mining techniques used to realize unseen patterns, including traditional statistical analysis and machine learning techniques. Students will analyze large datasets and develop modeling solutions to support decision making in various domains such as healthcare, finance, security, marketing, and customer relationship management (CRM). Models will include decision trees, clustering, principal component analysis, classification, k-means, ensemble methods and other supervised and unsupervised predictive models primarily for structured data. Students will also learn how to apply these models into production through business rules and SQL. Statistics and exposure to any programming language is required. The primary software tools for this class will be R. Prerequisite: BIA 6300, plus BIA 6309 and BIA 6311S equivalent knowledge.
BIA 6303. Predictive Models (2 credit hours)
The course will teach advanced statistical techniques to discover information and build predictive models from large sets of data. Emphasis is placed on applications for marketing research and operations. Methods will include expansion of linear models, neural nets, support vector machines, naïve bayes and Bayesian networks, collaborative filtering, propensity models market basket analysis, longitudinal data analysis and product launch models. Statistics and exposure to any programming language is required. Prerequisites BIA 6301, BIA 6309, BIA 6311, BIA 6312 or consent of the program director.
BIA 6304. Text Mining (2 credit hours)
This course will introduce the essential techniques of text mining, understood as the extension of data mining's standard predictive methods to unstructured text. Students will also learn web scraping techniques and collection of unstructured data from social media sites like Twitter, as well as a company web site. Students will also be introduced to sentiment analysis and natural language processing. Statistics and exposure to any programming language is required. The primary software tool for this class will be Python & R. Tableau will also be incorporated. Applied Data Mining is recommended prior to taking this course. Prerequisites BIA 6301, BIA 6311, BIA 6312 or consent of the program director.
BIA 6306. Web and Social Media Analytics (2 credit hours)
The primary focus of the course is the application of descriptive and predictive techniques to web analytics and other social media platforms including user behavior modeling and e-metrics for business intelligence. Students will also work with Google analytics and other web based analytical platforms to judge performance and ROI of a company’s web and social media programs. The primary software tool for this class will be Google Analytics and other web based tools. Prerequisite BIA 6300, BIA 6301 and BIA 6302 or consent of the program director.
BIA 6305. Big Data and Prep (2 credit hours)
This course will emphasize the extraction, transformation and preparation of data from traditional relational databases as well as more complex storage systems (such as Hadoop) for analytical purposes. Students will be introduced to data wrangling, munging and scraping of both structured and unstructured data. Students will also be introduced to parallel process for big data such as map reduce and query languages like HIVE. Exposure to any programming language is required. The primary software tool for this class will be Python as well as access to a standard rational database (Oracle or Mysql) and a Hadoop system. Prerequisites BIA 6301, BIA 6310, BIA 6311, BIA 6312 or consent of the program director.
BIA 6308. Strategy and Analytics (2 credit hours)
The focus of this class is the implementation of analytics as a competitive advantage across the enterprise. In this course, students will read case studies and hear from guest speakers about challenges and opportunities generated by the advent of “big data.” Students will make group presentations and write critical response papers related to these case studies. Students will consider some of the traditional business frameworks (e.g., SWOT analysis) for evaluating the strategic opportunities available to a company in the “big data” space. Prerequisite BIA 6300, BIA 6301 and BIA 6302 or consent of the program director.
BIA 6307. Dashboard Creation and Implementation (2 credit hours)
This course provides instruction for creating analyses and dashboards in business intelligence applications. Students will begin by building basic analyses to include in dashboards, with more complexity as the course progresses. Emphasis is placed using the proper metrics and ways to display them for different users. Dashboards will be built for implementation on both desktops as well as tablet devices. Students will also identify KPIs and how they may be used across different levels of the organization. Examples include human resources, recruiting, sales, operations, security, information technology, project management, customer relationship management and many more departmental dashboards. Students will also be introduced to analytical strategy models like the balanced scorecard. Prerequisite BIA 6300 and BIA 6302 or consent of the program director.
MG 6008. Managerial Communications (2 credit hours)
This course explores the various techniques, instruments, processes and styles that leaders employ to communicate effectively within organizations. Students write, give oral presentations and learn how to use electronic media effectively. Exercises employ numerous real or simulated business situations that require communication in different styles, using a variety of forms and methods. This course provides an introductory experience and orientation to the graduate program. It establishes common communication protocols, determines critical self-awareness profiles and identifies the Rockhurst themes that students apply throughout the program.
ACFN 6300. Financial Decision Making for Managers (2 credit hours)
This course is an investigation of financial decision making in business, government, and not-for-profit organizations. Emphasis is on the application of financial and nonfinancial information to a wide range of management decisions, from product pricing and budgeting to the project analysis and performance measurement. A variety of decision-making tools such as break-even analysis, activity-based costing procedures, contribution margins, budgeting and the balanced scorecard are included. Emphasis is also placed on preparing financial information to request new capital, personnel or projects. This course will focus on the interpretation and use of basic financial information by non-financial managers, not on production of financial statements and reports.
MG 6320. Project Management (2 credit hours)
This course introduces students to the process of project management that includes planning, implementation, progress measurement and performance, results and evaluation. Students will learn the knowledge, skills and technical tools for identifying project requirements, establishing project objectives and scheduling, balancing constraints and resources, and considering the needs and expectations of key stakeholders. Students will learn the trade-offs and balance of project scope, resources and schedule, and will learn how to compose an effective project management team. The course also covers producing project documentation, such as scope, requirements, design and testing documentation.
MK 6410. Marketing Strategy (2 credit hours)
This strategic marketing course gives you practice in the design, implementation and control of marketing strategies. It is an operationally oriented course in which the application and not the definition of marketing concepts, principles and methods are important. The course stresses integration of the major decision areas of marketing rather than the sequential discussion of these subjects.