Our teaching philosophy

Work your way up to the big leagues

Remember your first use of data? You probably used it to explain something that had already happened. Looking in the rearview mirror is just the starting point. Things get interesting—and more complex—when you get into predicting future events or determining the optimal set of decisions for a specific business outcome.

Our teaching philosophy and course sequence are designed to help you work your way up this data ladder—going from descriptive analytics (explaining what happened) to diagnostic, predictive, and prescriptive analytics (influencing what will happen).

Certificate and master's required courses

Master's degree sample course electives (four required)

Master's degree required experience project

See schedule of upcoming courses

Required courses

Data and Decisions (MSCI:9100 or MBA:8150) formerly Business Analytics

  • What's the sales value of a home in Des Moines? Create a price prediction model using market data.
  • What are the costs and benefits of bringing a pharmaceutical drug to market? Analyze the situation using structured decision analysis.
  • How many flu shots should be ordered for a clinic during an epidemic? Maintain high-quality service even in the face of substantial uncertainty.

Data Management and Visual Analytics (MSCI:6050)

  • Which zip codes had the highest increase in sales within a product category? Convert data needs into SQL queries and integrate SQL in an interactive visualization.
  • How can a nonprofit track donor engagement to provide more personalized and targeted promotional materials? Answer a business problem using data stored in a database management system.
  • Can I create an online dashboard for team KPIs? Transform live data into metrics using SQL queries and choose appropriate visualizations for query outputs.

Data Programming in R (MSCI:6060)

  • How do I automatically integrate sales data from separate data sources? Design a step-by-step procedure for solving a problem and then code it using the open-source R environment.
  • How can I download quarterly financials for multiple companies? Use advanced R features that extract data from websites.
  • Do customers who buy Product X also tend to buy Product Y? Write simple data-mining procedures that find associations and execute them repeatedly.

Advanced Analytics (MSCI:9110)
Prerequisite: Data and Decisions (MSCI:9100 or MBA:8150)

  • How did the 2001 terrorist attacks impact travel patterns and behavior in the United States? Determine hypothetical trends if the attacks had not happened using time series analysis.
  • How can I create an index fund to track a particular financial sector? Solve an optimization model to choose a representative sample of companies in which to invest.
  • How do companies use analytics? Present a case study of a large company using analytics successfully.

Data Science (MSCI:6070)
Prerequisite: Data and Decisions (MSCI:9100 or MBA:8150)

  • Will this stock price go up or down tomorrow? What about in the next 5 seconds? Identify opportunities for profitable trades.
  • Which of these people is most likely to respond to a direct marketing contact? Segment your customers for better targeting, and identify the most promising new leads.
  • What kind of approach might move a donor to a higher giving level? Conduct a design of experiments to gather the most information from your trial marketing campaign.

Master's degree elective courses

Data Programming in Python (MSCI:6040)
Prerequisite: None

  • How do I automatically combine data from separate sources?  Design a step-by-step procedure for solving a problem and then code it using the open-source Python environment.
  • How can I download real estate data?  Use advanced Python features that extract data from websites.
  • How can I use Python to do some basic artificial intelligence and machine learning?

Social Analytics (MSCI:6105)
Explore the collection, management, and analysis of social data(interactions among actors). Actors are individuals, organizations, or other collectives. Sources for social data include social media, websites, annual reports, press releases, articles and other traditional media. 

Text Analytics (Programming in R (MSCI:6060 or MSCI:9060) and Data Science (MSCI:6070) or Advanced Analytics (MSCI:9110)

  • How can I convert unstructured emails, tweets, blogs, customer reviews, etc. into insights? Learn how to identify relevant sources, harvest the data, manage large databases, and use techniques to change words into quantifiable metrics.

Big Data Management and Analytics (MSCI:6110)
Prerequisites: Data Management and Visual Analytics (MSCI:6050 or MSCI:9050) and Data Programming in R (MSCI:6060 or MSCI:9060)

  • What if my data set is too large to be handled by a single computer? Explore new concepts and technologies instead of traditional relational databases.

Applied Optimization (MSCI:6130)
Prerequisites: Data and Decisions (MSCI:9100 or MBA:8150) and Data Programming in R (MSCI:6060 or MSCI:9060)

  • How do we use optimization (also called prescriptive analytics or mathematical programming) to make tactical and strategic decisions? Learn advanced optimization skills including data collection and prep, logical modeling, and solution interpretation and implementation within a software environment.

Information Visualization (MSCI:6140)
Prerequisite: None

  • How do I make my data digestible for others in my organization by presenting it visually?
  • Which type of data graphic should I use in a given situation, and what makes each graphic type unique?
  • How does human perception affect how my data should be presented?
  • Which statistical methods can help me visualize information?

Financial Analytics (MSCI:6150)
Prerequisites: Data and Decisions (MSCI:9100 or MBA:8150) and Data Programming in R (MSCI:6060 or MSCI:9060)

  • How can business measure risk in the face of fluctuating treasury bond rates, equity prices, and foreign exchange rates? Learn the classical financial models and statistical and risk metrics, and scale them up with analytics techniques to find the best investments.

Healthcare Analytics (MSCI:6180)
Prerequisites: Data and Decisions (MSCI:9100 or MBA:8150) and Data Management and Visual Analytics (MSCI:6050 or MSCI:9050)

  • How do I maintain an electronic-medical-records system that supports high quality patient care?
  • What statistical methods are appropriate for healthcare applications?

Data Leadership and Management (MSCI:6210)
Prerequisite: None
How do I manage a team of analytics and IT professionals?
What are the best practices for a CIO (chief information officer) or other data manager?

Supply Chain Analytics (MSCI:9160)
Prerequisite: Data and Decisions (MSCI:9100 or MBA:8150)

  • How can I take a data-driven approach to supply chain management?
  • What are the best tools and techniques for forecasting demand?
  • How can advanced analytics be used to manage inventory?
  • What does it mean to share risk across the supply chain?

Digital Marketing Analytics (MKTG:9165)
Prerequisite: Data and Decisions (MSCI:9100 or MBA:8150)

  • How can I translate data into marketing strategy? Examine applications for product forecasting, product development, promotional strategy, online marketing, and customer databases.

Master's degree required experience project

Analytics Experience (MSCI:6120)
Prerequisites: All certificate courses plus at least one Master's elective

  • The knowledge you've gained in the program, particularly in the core courses, will culminate in a group project and/or competition that solves a real-world business problem. Groups may partner with an area business.

Next Steps