The Graduate Certificate of Completion in Business Analytics equips professionals with the technical and analytical skills needed to transform data into strategic insights. This four-course program blends foundational programming, data management, and advanced analytical techniques to prepare learners for data-driven decision-making in today’s competitive business environment. Students begin by developing core programming skills for data analysis and reporting, gaining hands-on experience with tools widely used in the analytics industry. They explore how to manage and structure data effectively, learning to design and utilize information systems that support business intelligence and operational efficiency. The program also introduces advanced analytical methods and data mining techniques, enabling learners to uncover patterns, forecast trends, and support proactive decision-making. Emphasis is placed on real-world application through case-based learning and the use of industry-standard software. By the end of the Certificate of Completion, learners will be able to manage complex datasets, apply analytical models, and communicate data-driven insights—making this program ideal for professionals seeking to enhance their analytical capabilities or transition into roles in business intelligence, data science, or analytics leadership.
Students seeking this certificate of completion will need to successfully complete:
(Click a course name below to view course details).
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.
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