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 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 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).

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.

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 applications of Python for business analytics. This class will focus on data extraction and manipulation as well as automating data analysis tasks to support the larger goal of improving business outcomes through data-driven insights. No prior programming experience expected.