Information Systems and Analytics

Professors: Narendra Agrawal (Benjamin and Mae Swig Professor), Gangshu Cai (Department Co-Chair), Manoochehr Ghiassi, S. Andrew Starbird, Andy A. Tsay

Emeritus Professors: Stephen A. Smith, Steven Nahmias

Associate Professors: Ram Bala, Tao Li , Haibing Lu (Department Co-Chair), David K. Zimbra, Sami Najafi-Asadolahi, Michele Samorani

Assistant Professors: Hussein El Hajj, Wilson W. Lin, Yu-Wei Lin, Xiaoyan Liu, Mohammad Amin Morid, Michele Samorani, Simrita Singh, Yaqiong Wang, Xiang (Shawn) Wan

Lecturers: Thunyarat (Bam) Amornpetchkul, Homi Fatemi, Rick Schaffzin, Sumana Sur, Xuan Tan, Xiaochen Zhu

Information Systems and Analytics Curriculum

OMIS 3000. Business Analytics

Business Analytics is the scientific analysis of data to make better business decisions. Students in this course will learn to use analytics platforms across a wide variety of applications such as marketing, finance, and supply chain management. They will become familiar with current technological environments for statistical/machine learning and visualization. Prerequisite: OMIS 3202. (4 units)

OMIS 3200. Quantitative Methods

Introduction probability and statistical analysis, emphasizing applications to managerial decision problems. Discusses descriptive statistics, probability theory, sampling distributions, statistical estimation, hypothesis testing, and simple and multiple regressions. Additional topics may include exploratory data analysis, analysis of variance, and contingency tables. Prerequisites: None. (2 units)

OMIS 3202. Analytical Decision Making

This course covers how to rigorously formulate decision problems, understand mathematical optimization, deal with the uncertainties inherent in real business problems, while introducing computer modeling tools like important Excel add-ons, R, Mathematica, CrystalBall, and \@Risk. Prerequisites: OMIS 3200. (2 units)

OMIS 3250. Analysis, Design, and Management of Enterprise Platforms

Introduces the information technology infrastructures that enable within and across firm operations, and the competitive advantages that information technology can offer various firms. Focuses on how firms effectively utilize information technology resources in their business models and operations. Prerequisites: OMIS 3200. (2 units)

OMIS 3252. Operations Management

This course introduces how firms get the right products and services to the right people, in the right place, at the right time and cost. In addition to firms that provide physical goods, this course covers information-enabled, supply-demand matching networks like Uber and AirBnB that vastly reduce cost and increase convenience in operationally intensive industries. Prerequisites: OMIS 3202. (2 units)

OMIS 3366. Database Management Systems

Introduces database management and database management systems (DBMS). Teaches technical and managerial skills in database planning, analysis, logical design, physical design, implementation, and maintenance. Features hands-on training in database design, development, and implementation using relational DBMS software. Emphasizes designing and developing reliable databases to support organizational management. Cross-listed as MSIS 2403/2503/2603. Credit will not be given for both. Prerequisite: Computer experience. (2 units)

OMIS 3372. Information Systems Analysis and Design

Examines methodology to assist in analyzing and designing computer-based information systems for business applications. Features tools including data flow diagrams, flowcharts, Structured English, pseudo code, hierarchy charts, structure diagrams, and Warnier-Orr charts. Requires applying these tools to a systems development project. Cross-listed as MSIS 2602. Credit will not be given for both. Prerequisite: None. (4 units)

OMIS 3374. Artificial Intelligence

Provides a survey of basic concepts in artificial intelligence and their applications to business-oriented problems. Includes production systems, search techniques, knowledge representation, and inference techniques as well as calculus, statistical and probabilistic reasoning, design and implementation of expert systems, and understanding natural languages. Entails application developments using Expert System shells. Prior knowledge on statistics and programming are required. (4 units)

OMIS 3378. Information Systems Policy and Strategy

Studies strategic management and deployment of information systems and technologies (ISTs) to improve business competitiveness. Examines the role of IST strategy in enabling companies to effectively manage in the turbulent and dynamic business environment brought about by the Internet. Analyzes new business opportunities in electronic commerce brought about by ISTs, including organizational redesign that these technologies require. Considers implementation and change management issues related to IST deployment in the new environment. Focuses on drawing lessons from the experiences of leading companies that are deploying ISTs to define and support their e-commerce strategies. Cross- listed as MSIS 2604. Credit will not be given for both. Prerequisite: None. (4 units)

OMIS 3384. Supply Chain Management

Focuses on the key challenges and issues relating to design, analysis, and management of supply chains to gain competitive advantage. The goal of the course is to assess supply chain performance and improve execution by effectively managing inventory, capacity, logistics and supply chain relationships. Additional topics include the role of information technology in this context, supply chain network design, and managing supply chains in environments with product innovation and proliferation. Prerequisite: OMIS 3357 or OMIS 3252. (4 units)

OMIS 3385. Supply Chain Analytics

This course will introduce students to a selection of important problems from all key areas of SCM-Plan, Source, Make and Distribute. Through real world case studies, students will learn about the broader business context within these problems. They will learn how to apply appropriate descriptive and prescriptive techniques to solve these SC problems, and the use of cloud based technology platforms to store, access, visualize and analyze data to make and communicate effective decisions. Prerequisites: OMIS 3000. (2 units)

OMIS 3386. Business Intelligence and Data Warehousing

Introduces technologies and managerial issues related to data warehousing, business intelligence, decision support systems, data mining, Web mining, and customer relationship management. Teaches technical and managerial skills in using and developing decision support applications. Emphasizes learning how to derive business value from large amounts of data. Provides hands-on training using a variety of BI tools. Cross-listed as MSIS 2621. Credit will not be given for both. Prerequisite: OMIS 3366 or instructor approval. (4 units)

OMIS 2390/3390. New Product Development

Introduces students to the methods companies use to develop and release new products. New product development is a challenging, rewarding activity that can make the difference between success or failure for a company, especially in technology-based industries. The traditional view that new product development is an "art" practiced by engineers has now given way to an understanding that it is a discipline that must be learned and practiced to be successful. Examines the sequence of activities needed to successfully develop and launch a new product or service; understand how the different functions and roles in product development interrelate and work together; learn how to balance strategic and tactical activities in successful product development; develop a better understanding of how to determine and satisfy customer needs; understand the financial aspects of product development; develop the skills to analyze and improve product development efforts within a company. (4 units)

OMIS 3391. Accelerating Innovation

This course introduces how contemporary organizations procure innovation ingredients (technology, IP, new business models), from outside the company, through deal-making, to fill gaps and get faster time-to-market. It also covers a 3-box framework, to recognize and manage inherent operational conflicts encountered, as companies innovate new business models, while maintaining current ones. Students lean practical deal-making skills to drive innovation, such as analyzing what external resource(s) (including IP) a firm wants for achieving its strategic intent, finding and selecting who to partner with, structuring and negotiating business contracts, and managing the deal to extract potential synergies. Student teams also study business development activities of a company. Prerequisites: None. (4 units)

OMIS 3392. Econometrics for Business Analytics with R

This is a 4-unit course designed in two parts. The 3 unit lecture session introduces a broad set of econometric tools to analyze large-scale real-world company data to make data-driven business decisions. The 1-unit lab session features hands-on training in practical data analytics skills using the powerful statistical software environment R. Topics include the Ordinary Least Squares (OLS), model selection, Generalized Least Squares (GLS), instrumental-variables regression, quantile regression, count data models, binary outcome models, and selection models. Prerequisites: ECON 3000. (4 units)