Course Listing For Business Analytics Courses

This course focuses on statistics used in business analytics, and is designed for students with little or no background in statistics but have a basic familiarity with data and spreadsheets. This course emphasizes project-based learning using Google Sheets and Python to apply basic statistical techniques to data modeling.

This course is designed as the entry point to learning SAS programming language and analytics programming concepts to gain business intelligence. It provides the tools necessary to write SAS programs to perform data management, analysis, and reporting including the creation of simple reports and computing basic statistics on data set variables. Hands-on exercises designed to facilitate understanding of business systems and business processes are included. The course also provides the basis for more advanced work in business analytics and advanced programming techniques for data modeling. This course aligns with the SAS Base Programming certification concepts.

This course introduces students to the fundamentals of Business Analytics. It aims to develop an understanding of analytics to develop business intelligence in a business environment. Students will learn project management by identifying business requirements, business processes, and stakeholders. This course emphasizes data management: cleaning, data modeling, forecasting using visualization, analyzing, and communicating data insights to stakeholders.

This course is designed to introduce students to the fundamentals of Structured Query Language (SQL) for the purpose of data management. Students will learn to identify the role and structure of relational databases as they apply to business analytics, apply the SQL in MySQL for data manipulation language (DML), apply the SQL in MySQL for data definition language (DDL), and apply normal forms (1NF, 2NF, & 3NF) for database normalization. Emphasis will be on ensuring data quality as it relates to business intelligence.

This course offers an in-depth exploration of topics in the field of data and information management from an applied perspective with an emphasis on data warehouses. The course is designed to provide not only a strong theoretical foundation, but also the technical skills required in analyzing, designing, implementing, managing, and utilizing information repositories. A variety of topics are covered that include relational database model, data modeling, and database design.

This course introduces an analytical toolset to address business problems. The course provides an overview of the key concepts, applications, processes and techniques relevant to data modeling for business intelligence. The course makes use of SAS Enterprise Miner to illustrate the use of business analytics methodologies to enhance decision-making.

This course provides an in-depth discussion on the data warehousing, data mining, analytics used for business intelligence. A variety of data analysis tools will be used to discover patterns and relationships in data that may be used to make proactive, knowledge-driven decisions. The course provides an in-depth discussion on various techniques of data mining including data modeling, pattern recognition, predictive analytics, and text mining. Prerequisite: BAN 400

This course is designed to introduce students to the fundamentals of using Tableau Desktop in the context of business and data analytics. Students will learn to demonstrate data visualization in the data analysis process to efficiently wrangle and analyze real-industry data. Exploration of data as it relates to business requirements and business processes will include determining data quality criteria and data modeling techniques through the use of dashboards to create business intelligence.

This course is designed to introduce students to the fundamentals of using Tableau Desktop in the context of business and data analytics. Students will learn to demonstrate data visualization in the data analysis process to efficiently wrangle and analyze real-industry data. Exploration of data as it relates to business requirements and business processes will include determining data quality criteria and data modeling techniques through the use of dashboards to create business intelligence.

This course is designed to provide a foundation of SAS analytics programming concepts and environments. It provides the tools necessary to write SAS programs to perform data management, analysis, and reporting. Topics include creating and documenting data sets, managing and reshaping data, writing reports, computing statistics on data set variables, and performing effective SAS programming. Hands-on exercises designed to facilitate understanding of all the topics are included. The course also provides the basis for more advanced work in data analytics and advanced programming techniques for data management. This course aligns with the SAS Base Programming certification concepts offered through the SAS Institute, Inc. Prerequisite: None

This course offers an in-depth exploration of all the major topics in the field of data and information management from an applied perspective with an emphasis on data warehouses. The course is designed to provide not only a strong theoretical foundation, but also the technical skills required in analyzing, designing, implementing, managing, and utilizing information repositories. Topics covered include relational database model, data modeling, logical and physical database design, structured query language (SQL) implementation, procedures and triggers, data integration and quality, data warehouses and other relevant techniques for addressing big data issues in organizations today. The strategic roles that data and information play in business operations, customer relationship management, business decision-making, and strategy development are also discussed.

This course provides an analytical toolset to address modern, data-intensive business problems. To be effective in a competitive business environment, a business analytics professional needs to be able to use analytical tools to translate information into decisions and to convert information about past performance into reliable forecasts. Using a case-based approach, the course provides an overview of the key concepts, applications, processes and techniques relevant to business analytics. The course makes use of the leading software products to illustrate the use of business analytics methodologies to enhance business decision-making. Prerequisite: None

As business organizations collect more and more data as a byproduct of their operations, decision-makers are beginning to proactively and systematically analyze these data to improve decision quality. This course focuses on topics relevant to data mining, which is the process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make proactive, knowledge-driven decisions. The course provides an in-depth discussion on various techniques of data mining including predictive modeling, pattern recognition, prescriptive analytics, and text mining. Both the theoretical and practical aspects of data mining are discussed in this course. Prerequisite: BAN 600.