Skip to Main Content

Business Analytics & Information Systems Toolkit

BAIS courses


BAIS curriculum

List of skills and activities in courses taken by all BAIS students.


BAIS:3020 - Computational Thinking:

Coding or programming is considered a must-have job skill for business and other professionals. However, it is much more than that. Coding is a way of thinking about problems and solving them with the use of computers. Python is one of the most popular languages for writing general-purpose programs. In this class, we learn to solve problems by writing Python programs.


Students will learn:

  • Anaconda programming environment
  • Python programming language, including:
    • Variables and functions
    • Loops and logic
    • String manipulation
    • Structured types
    • Dictionaries
    • Exceptions
    • Object oriented programming
    • Plotting
    • Libraries


Students will be able to:

  • Write robust Python applications that utilize multiple functions
  • Solve problems using techniques such as:
    • exhaustive enumeration
    • approximation
    • bisection search
  • Scrape web pages for data
  • Perform text analytics on data
  • Produce visualizations
  • Process images



BAIS:3200 - Database Management:

Due to exponentially growing computation power and storage capacity, as well as the as increasingly digital nature of business operations, modern organizations collect and store a wealth of data about their interactions with various stakeholders, including customers, employees, shareholders, government, and suppliers. It is critical to manage data effectively so that it supports business strategy and provides competitive advantage. In this class, we learn the core concepts needed to design and utilize database management systems (DBMS) and Structured Query Language (SQL).


Students will learn:

  • Data modeling
  • Relational database design and normalization
  • Physical implementation of databases
  • SQL language & syntax
  • Database applications


Students will be able to:

  • Draw Entity Relationship and Enhanced Entity Relationship diagrams to represent data and business rules
  • Create logical models of databases, including normalization to third normal form
  • Construct relational database tables with SQL commands
  • Manipulate and load data into a database using database management software
  • Perform SQL queries, including:
    • Joins
    • Sub-queries
    • Compound queries
    • Conditional logic
  • Build a Web-based database application



BAIS:3050 - BAIS Professional Preparation:

This course is an introduction to the many career avenues available to a BAIS major and how to successfully search for for and landing one of those careers. Along the way students will be guided as they build their personal brand and prepare for their future internships and careers.


Students will learn:

  • To write a technical resume
  • To navigate technical interviews
  • To navigate case interviews
  • different careers in BAIS
  • Utilizing Career Service's tools and professionals
  • Life in BAIS from an industry panel
  • Negotiating the offer!


Students will be able to:

  • Better understand career opportunities within the business analytics and information systems field
  • Learn about the course curriculum - including the capstone course and additional educational options
  • Identify how to best manage your career search - from creating a technical resume to managing applications to networking and more
  • Learn about the industry from leading experts
  • Understand various types of interviews (behavioral, technical, case) and have the opportunity to practice your interview skills
  • Gain an understanding of the importance of hard and soft skills required in the workplace
  • Learn how to translate your knowledge and skills to match job posting requirements



BAIS:3250 - Data Wrangling:

"Data wrangling" encompasses collecting, cleaning, transforming, integrating, and describing data. It is estimated that data scientists spend up to 80% of their time on data wrangling tasks. In addition to being the most time-consuming step of most analytics workflows, wrangling is critical, as it impacts the outcome of all subsequent experiments/analyses. This course introduces essential R programming skills for data wrangling.


Students will learn:

  • R and R Studio
  • File Handing
  • Data Cleaning and Transformation
  • Web Scraping
  • APIs
  • Data Integration
  • Descriptive Analytics and Visualization


Students will be able to:

  • Build foundational programming skills, including variables, data types, data structures, functions, and subsetting
  • Read and write plain text, delimited, and nested file formats (XML, JSON), including file encoding
  • Learn methods to identify and correct common types of errors, handle missing values, and create derived features
  • Access data via APIs, Web scraping, and external database connections
  • Perform vertical and horizontal data integration
  • Use statistical methods (summary tables, hypothesis testing, regression) and visualizations to describe data
  • Apply techniques for time-series analysis and text analytics, including regular expressions and term frequency representation



BAIS:3500 - Data Mining:

In this course you will learn the basic concepts and techniques of data mining and knowledge discovery as applied to business problems. The focus will be on using recent data mining software to solve practical problems. Students will learn the process of turning raw data into intelligent decisions, and the algorithms that are commonly used to build predictive models and find relevant patterns in data.


Students will learn:

  • R programming
  • Knowledge discovery process
    • data mining problem formulation
    • data cleaning & transformation
    • data visualization
    • model evaluation & comparison
    • dimensionality reduction
  • Predictive modeling techniques
    • regression
    • decision trees
    • support vector machines
    • artificial neural networks
    • Ensemble Models
      • Random forest
      • Adaboost
      • Gradient boost
  • Clustering
    • hierarchical clustering
    • k-means
  • Model evaluation metrics


Students will be able to:

  • Understand the business prediction and model selection process
  • Discuss their theoretical appreciation for a variety of data mining methods
  • Apply practical knowledge of the uses and limitations of data mining
  • Build data mining models to solve practical problems using a software package
  • Evaluate, compare and select models using a variety of metrics



BAIS:4150 - Business Analytics and Information Systems Capstone:

The purpose of this course is to allow students to gain exposure to practical, real-world applications of the concepts they have encountered throughout the BAIS curriculum. Students will gain relevant analytics project experience by working in teams with a sponsor institution. Projects explore data-based topics of business interest to each sponsor. Significant time outside of class will be required to complete the deliverables of the project AND deliver value to project sponsors.


Students will learn:

  • Project management skills for data analytics projects
  • To clarify problems and document accurate problem statements
  • How to effectively provide weekly progress reports and status updates
  • Working within a professional team, including how to give constructive feedback to team members


Students will be able to:

  • Apply concepts from all Tippie College of Business core courses to help organizations understand their problems and potential impact of solutions
  • Organize, manage, and execute analytics projects to help organizations solve problems
  • Apply concepts from all BAIS courses to help solve those problems
  • Lead status meetings with their project sponsor
  • Implement a software solution to analyze data from the project sponsor
  • Summarize and present process, findings, and recommendation to project sponsor

List of skills and activities in BAIS elective courses.


BAIS:3800 - Optimization and Simulation Modeling: (offerings planned fall & spring semesters)

In Optimization and Simulation Modeling, students learn the art and science involved with translating a business problem stated in layperson’s terms into a mathematical model that can provide actionable insight for the decision-maker. Students learn to assess the business problem, acquire the appropriate data, and formulate a mathematical model that captures the essential elements of the decision-making problem. Using spreadsheet software, students will learn how to employ data to guide business decisions in areas such as operations, accounting, finance, marketing, economics, and human resources.


Students will:

  • Understand what factors make a decision difficult and identify the appropriate modeling technique (optimization or simulation)
  • Formulate optimization models by identifying the business objective and constraints and stating these in terms of decision variables
  • Understand the difference between linear and nonlinear optimization models and the implication of this difference
  • Model logical conditions using binary decision variables
  • Use data to model uncertainty via probability distributions
  • Construct Monte Carlo simulation models to quantify risk



BAIS:4280 - Cybersecurity: (offerings planned spring semesters)

Cybersecurity features frequently in media headlines and movie plots. But more importantly, it is also one of the fastest-growing sectors within business analytics and information systems. This course will discuss current trends in data and network security as well as the techniques necessary to ensure the confidentiality, integrity, and availability of information assets. Because cybersecurity involves every member of an organization, we will examine these topics from multiple perspectives (e.g., IT administrator, CEO, home user, hacker). The goal of this course is to increase all students' awareness of a broad range of issues in cybersecurity and develop a security mindset, no matter their career path.


Students will learn:

  • Best practices/NIST framework
  • Risk assessment/risk management
  • Cryptography
  • Access and identity management
  • Database security
  • Application and network security


Students will be able to:

  • Identify data assets and assess the risks of potential threats
  • Send and receive encrypted messages
  • Write a secure password policy and discuss multi-factor authentication alternatives
  • Understand various types of cyberattacks as well as prevention and mitigation strategies for each
  • Maintain security in a database environment, including protecting data integrity and configuring accounts and privileges



BAIS:3025 - Business Process Automation: (offerings planned fall semesters)

In this course, you will learn how business processes can impact your product, your customers (or users), and your business. We will first learn to map and measure business processes in their current state accurately. We will then utilize tools and techniques from Lean to make processes more efficient, from Six Sigma to identify the root cause of problems and 5S to simplify process steps. We will practice implementing these new skills manually before learning to utilize process mining to help with extensive, complex business processes.

Finally, we will learn to identify processes and steps ready for automation. Through process automation, we can reduce the variability of our output and free our employee's time for tasks that require skill and thinking. We will use various parts of Microsoft Power Platform to learn how to create practical applications and automation in no code/low code environments.


Students will learn how to:

  • Measure business processes using metrics such as process time, flow time, wait time, lead time, bottleneck, etc.
  • Diagram different business process maps
  • Process mining using Celonis Execution Management System
  • Fundamentals of robotic process automation
  • Create and maintain Microsoft SharePoint Lists
  • Build and run automated tasks using Microsoft Power Automate
  • Develop applications using Microsoft Power Platform no-code development environment


Students will be able to:

  • Create detailed current, ideal, and future state value stream maps.
  • Earn Celonis, Academic Process Mining Fundamentals credentials
  • Build a complete RPA solution using components of the Microsoft Power Platform



BAIS:3140 - Information Visualization: (offerings planned fall semesters)

Information Visualization is the art and science of turning raw data into something that can be understood and utilized by both technical and non-technical audiences to make evidence-based decisions. We will explore the process of turning raw data into useful information that tells a story and then present that story in a way that technical and non-technical audiences can use it to make decisions. It may help to think of this course as “graphic design for data”.


Students will learn:

  • The concept of Data Graphics
  • Data exploration and graphical representation
  • Visual design practices and techniques
  • Analytical design principles
  • Visualizing distributions
  • Revealing temporal change
  • Visualizing relationships
  • Visual storytelling


Students will be able to:

  • Present analytical results
    • Visually through reports and presentations
    • Interactively through digital formats
  • Utilize commercial tools such as Tableau and Excel to support visual storytelling
  • Create useful, easy to use, dashboards
  • Create compelling storyboards



BAIS:4220 - Advanced Database Management and Big Data: (offerings planned spring semesters)

Contemporary firms of all sizes store a wealth of data about their interactions with various stakeholders, such as customers, employees, shareholders, government, suppliers, and so on. Modern database management systems (DBMS) have long been used to store and manage massive data and are a crucial component of modern business intelligent systems. This course will build on skills learned in BAIS:3200 – Database Management to help students learn advanced querying and database management skills as well as introduce students to the top of "big data".


Students will learn:

  • Deeper knowledge of relational database principles and concepts
  • Advanced SQL and PL/SQL programming skills
  • Data quality, triggers and transaction management
  • Basic theories of big data, cloud computing, distributed databases, Hadoop, and HiveQL


Students will be able to:

  • Write advanced SQL queries (e.g., nested query) on Oracle database
  • Utilize Procedural Language extensions to the Structured Query Language (PL/SQL) code for data management and analysis on Oracle Database
  • Use stored procedures and triggers to interact with relational database management systems (RDBMS)
  • Understand the basic idea of the Hadoop system and MapReduce. Write basic HiveQL queries to process large data using Hive and Spark.



BAIS:3300 - Digital Project Management: (offerings planned spring semesters)

We designed the course to give students a broad understanding of what happens behind the scenes with digital products. In the end, students have various skills, from managing to producing digital products. 

The class identifies opportunities through customer journey mapping, followed by setting and managing strategy using objectives and key results (OKR) and key performance indicators (KPI). Next, we learn about Scrum roles, artifacts, and rituals used to manage products in an Agile environment. Finally, students work to enhance their technical skills by improving HTML literacy, managing source code, building small web applications using APIs, writing automated tests, building simple CI/CD pipelines, and deploying their products to Microsoft Azure.
Students will practice these new skills by building portfolio websites.


Students will learn:

  • To draw customer journey maps
  • To write objectives and key results for a product
  • To write accessible, valid HTML that conforms to WCAG 2.2 standards
  • To design inclusive, user-friendly input forms
  • Source code management using Git and GitHub
  • Writing automated tests using PyTest
  • Build continuous integration/continuous deployment (CI/CD) pipelines using GitHub Actions


Students will be able to:

  • Identify opportunities for existing digital products
  • Manage strategy and day-to-day activities for building digital products
  • Manage and make a personal portfolio website from idea to deployment. 



BAIS:3400 - Cloud Computing: (offerings planned fall semesters)

Cloud Computing provides foundational concepts to understand communication on the Internet and practical hands-on learning in the Microsoft Azure cloud environment. Students learn to create and manage Azure accounts and the cloud environment and configure specific resources in Microsoft Azure.

At the end of class, students will have the knowledge and skills to pass the entry-level Microsoft cloud certification exam. The course final exam is the AZ:900 - Microsoft Azure Fundamentals certification exam provided on campus and at no additional cost to the student.


Students will learn:

  • Public and private IPv4 addressing, as well as IPv6 addressing
  • Purchase a domain name and configure DNS services to use that domain to access cloud resources
  • Managing Microsoft Azure accounts and cloud environment
  • Configuring Microsoft Azure resources
    • Virtual machines
    • File storage
    • Database storage
    • Application services
    • Logic apps
    • Function apps
    • Virtual networking


Students will be able to:

  • Articulate benefits and opportunities using cloud computing
  • Describe the technology and concepts necessary to provide publicly available resources in the cloud
  • Configure Microsoft Azure resources for compute, storage, and networking
  • Pass the AZ:900 - Microsoft Azure Fundamentals certification exam



BAIS:3600 - Data Engineering: (offerings planned spring semesters)

Data Engineering is a growing discipline with more opportunities to store and process Big Data and to contribute to business' data-informed decision-making. Building upon foundational skills that intersect with security, data architecture, and software engineering, students will leave this class with essential skills to engineer data pipelines at scale.


Students will learn:

  • Learn advanced data principles that will be transferable to any technology stack 
  • Continue to build upon previous coursework to advance their SQL and Python skills 
  • Build skills to work in modern data ecosystems that include disparate data types and formats 
  • Demonstrate knowledge of the data lifecycle through hands-on assignments  
  • Take the DP:900 - Microsoft Azure Data Fundamentals certification exam


Students will be able to:

  • Configure and manage a cloud-based data environment (using Azure)
  • Generate and maintain scalable data infrastructures through quality query-writing and storage optimization
  • Develop data pipelines with both relational and non-relational data
  • Utilize data to produce effective analytics and data visualizations


List of BAIS elective courses offered in other departments.


CS:1210 - Computer Science I:Fundamentals:

This elective course is offered through the Computer Science department in the College of Liberal Arts and Sciences.



ECON:3355 - Economic and Business Forecasting:

This elective course is offered through the Economics department.



MKTG:3102 - Marketing Analytics:

This elective course is offered through the Marketing department.



BAIS:3100 - Accounting Systems and Analytics:

This elective course is offered through the Accounting department.



STAT:4540 - Statistical Learning:

This elective course is offered through the Statistics department.