Business Analytics

  • Department Information

    Business Analytics

    The Analytics and Operations Department provides instruction in this area.

    Doug Bosse, Chair
    Professors Ashworth, Bosse, Eynan, Harrison, Ho, Tallman
    Associate Professors Coughlan, Thekdi, Thompson, Whitaker
    Assistant Professors Aronson, Chen, Courtney, Cruz, Mattson, Sutton


  • Concentration

    The Business Analytics Concentration

    The Analytics and Operations Department offers a concentration in business analytics. This four-course concentration provides students with the tools and technologies to analyze data for business applications. The business analytics concentration includes coverage of software such as SAS (Statistical Analysis Systems), SQL (Structured Query Language), and Python programming language, with applications in business process optimization and machine learning.

    Business analytics can only be taken as a secondary concentration by students who have a primary major in accounting or economics (business), or another primary concentration in business administration (accounting, economics, finance, international business, management, marketing).

    Requirements:

    INFO 201 Data Analysis Software

    INFO 301 Advanced Applied Statistics

    INFO 302 SQL and Process Optimization for the Business Analyst

    INFO 303 Machine Learning for the Business Analyst

    In addition to the four required INFO courses in this concentration, students are recommended to take one related course in their primary concentration or major such as:

    ACCT 307 Accounting Information Systems

    ECON 370 Advanced Econometrics

    ECON 372 Advanced Macroeconomics

    FIN 461 Cases and Financial Modeling

    MKT 423 Marketing Analytics

Courses

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  • INFO 201 Data Analysis Software

    Units: 1

    Description

    Software tools and technologies to analyze data for business and economics applications. Topics include SAS (Statistical Analysis System), SQL (Structured Query Language), and Python programming language.

    Prerequisites

    BUAD 202.

  • INFO 301 Advanced Applied Statistics

    Units: 1

    Description

    Regression and simulation methods to solve complex problems in business, society, and the public sector. Selection of the correct statistical technique for the particular problem being solved, running statistical analyses using analytics tools that are commonly used in industry (e.g. SAS, SQL, and Python), and proper interpretation of the results to support data-driven decisions. Topics include regression analysis, limited dependent variable estimation, survival functions, and simulation.

    Prerequisites

    MGMT 225 and INFO 201.

  • INFO 302 SQL and Process Optimization for the Business Analyst

    Units: 1

    Description

    Introduces common techniques for relational data management, including conceptual modeling and Structured Query Language (SQL). Additionally covers topics from business process re-engineering, with a focus on process modeling, performance assessment and how process improvement influences database design.

    Prerequisites

    MGMT 225 and INFO 201.

  • INFO 303 Machine Learning for the Business Analyst

    Units: 1

    Description

    Process of investigating data through a machine learning lens. Application of machine learning techniques to real-world business use cases. Extract and identify useful features that best represent data, some of the most important machine learning algorithms, evaluate the performance of machine learning algorithms, and presentation (visualization) of results to business stakeholders.

    Prerequisites

    MGMT 225 and INFO 201.