Overview of where business analytics fits into current corporate decision-making support; intro to the three major aspects of business analytics (descriptive, predictive and prescriptive). Emphasis begins with analytics’ use in addressing business problems and opportunities (applications) rather than programming and statistical underpinnings. The review of statistics, Excel and the scientific method are incorporated to analytic thinking for decision-making. Concentrates on data issues (such as data preparation, transformation and cleaning) as well as descriptive and visual analytics. Introduces students to the leading data visualization software packages used in business organizations and apply them using a variety of business, economic and government data sets.

Addresses the most valuable predictive and descriptive modeling methodologies and how they address sales & marketing, supply chain, finance, accounting and HR business problems/opportunities – classification, regression, behavioral, value and optimization modeling; demand and adoption forecast models; and market basket analysis (association and sequence). Also focusses on developing an understanding which analytical tool can be used for which purpose, and the limitations and benefits of each. Hypotheses testing, sampling issues, analysis rules and best practices for analysis are also explored.

SNC/UNC grade assessment.

Addresses the unstructured data management skills needed for modern data analysis including those salient to big data and real-time data environments. Introduces unstructured data, including both well-formatted data (XML, JSON etc.) and free flowing information. Learn about software and databases as well as methods for identification, acquisition, extraction, validation/cleansing, representation and analysis of data for organizational use. Learn how to store and manipulate unstructured data, how to mine text and how to manipulate and analyze unstructured data to enable better decision-making. Briefly introduces data visualization tools as a way to communicate effectively insights gained from analyzing unstructured data.

Takes insights derived from the analytics and focusses on how to communicate these actionable insights to executives for decision-making purposes. Includes presentation and storytelling skills, and the ability to communicate to both technical and managerial audiences. Students also need to be able to measure the outcomes based on the decisions that were made with the data-storytelling. Looks to develop good listening and team building and other communication skills.

A team-based course that gives students the opportunity to further apply the content learned in prior courses to a company-specific set of business problems/opportunities. Combines course work with a student-team practicum with a local area company that provides a real business problem/opportunity and a real-life/messy data set. Depending on the number of companies involved and the size of the class, there can be multiple companies or a single company involved. For the latter, the project is set up as a competition for the best-fitting solution.

Lectures and discussions in an area which, because of its topicality, is not the subject of a regular course. Topics are designated in the Schedule of Classes.

S/U grade assessment.

S/U grade assessment.