This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL). This course also covers visualization, reporting, and dashboard design with experiential learning using leading industry applications.

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL). This course also covers visualization, reporting, and dashboard design with experiential learning using leading industry applications.

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL). This course also covers visualization, reporting, and dashboard design with experiential learning using leading industry applications.

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL). This course also covers visualization, reporting, and dashboard design with experiential learning using leading industry applications.

The service sector contributes about 70% of the gross domestic product of the US economy. Also, it accounts for about 75% of the US employment. This course in "Service Industry Operations" examines firms in the service sector. The course begins with highlighting the salient aspects of services (specifically, differentiating a service from a product on various dimensions), and then provides an overview of structural, infrastructural, and behavioral aspects of managing service operations. In particular, we will consider service process, service quality, service design, service failures, and new (digital) advancements in service delivery. The course is intended to provide managers in the service sector with knowledge and tools to make informed decisions such as process improvements, wait line management, and demand and yield management. The course will impart both quantitative and qualitative analysis skills, especially those needed for managing important business tradeoffs within the context of services. Using a blend of cases, selected book chapters, and articles from business press and academic literature, this course will explore the aforementioned concepts in diverse service industries including healthcare, retail, hospitality, transportation, and financial services.

Computer simulation presented for carrying out trial-and-error experiments on computer approximations of real, management systems. The goal is to 1) validate a new idea quickly, 2) diagnose potential product design problems, 3) optimize performance of complex systems, and 4) learn about something complex. The Arena environment, based on the SIMAN language, used to build models and video game-like animations.

Quality control concepts including: fundamental computer and statistical concepts: Statistical Process Control (SPC) using control charts; methods for quality improvement; acceptance sampling; industrial experimentation and reliability.

The most frequently used methods in modeling and analyzing business and economic problems. The process of abstracting and model building, and the role of various types of models in description and decision making.

This course provides an introduction to advanced spreadsheet techniques and programming using macros and Visual Basic for Applications (VBA) in Excel. The focus is on automation of repetitive tasks, including data manipulation as well as data analysis. Experience with Excel is recommended. No prior programming experience expected.

This course provides an introduction to advanced spreadsheet techniques and programming using macros and Visual Basic for Applications (VBA) in Excel. The focus is on automation of repetitive tasks, including data manipulation as well as data analysis. Experience with Excel is recommended. No prior programming experience expected.