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ANLY 6020: Business Analytics II

3.00 Credits

Southern Utah University

A continuation of ANLY 6010. Covers the primary analytic techniques involved in data mining for business problem-solving, including advanced regression, decision trees, kNN, and others. Introduces unsupervised learning methods. Builds on the programming skills established in Business Analytics I. (Fall - 2nd Session, Summer - 1st Session) [Graded (Standard Letter)] Prerequisite(s): ANLY 6010 - Prerequisite Min. Grade: C Registration Restriction(s): MAcc or MBA students only Prerequisite: ANLY 6010

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ANLY 6030: Data Management and Visualization

3.00 Credits

Southern Utah University

An introduction to the methods and tools for database management and data visualization with a particular focus on industry analytics. Database topics include the logical structure of databases as well as the methods and technology for efficient data storage, retrieval, and presentation. Visualization topics include an overview of the Tableau software for data visualization and discussion of data visualization principles. Emphasizes skills in retrieving and presenting data for business presentation. (Spring - 1st Session, Summer - 2nd Session) [Graded (Standard Letter)] Registration Restriction(s): MAcc or MBA students only

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ANLY 6050: Programming for Data Science

3.00 Credits

Southern Utah University

Introduction to programming basics, binary computation, problem-solving methods and algorithm development. Includes procedural and data abstractions, program design, debugging, testing, and documentation. Covers data types, control structures, functions, parameter passing, library functions, arrays, inheritance and object-oriented design. Laboratory exercises in Python. (Fall - 2nd Session, Summer - 1st Session) [Graded (Standard Letter)] Registration Restriction(s): Master of Science in Business Analytics

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ANLY 6100: Data Analytics I

3.00 Credits

Southern Utah University

An introduction to data science methods in business, finance, and economics. Includes an introduction to an appropriate programming language for data manipulation and modeling. Provides an overview of descriptive, predictive, and prescriptive methods in data analytics. (As Needed) [Graded (Standard Letter)] Prerequisite(s): BA 6000 or MGMT 6100 - Prerequisite Min. Grade: C Prerequisite: BA 6000 O MGMT 6100

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ANLY 6110: Data Analytics II

3.00 Credits

Southern Utah University

A continuation of ANLY 6100. Covers the primary analytic techniques involved in data mining, including logistic regression, decision trees, kNN, naive Bayes, and others. Introduces unsupervised learning methods. Builds on the programming skills established in ANLY 6100. (As Needed) [Graded (Standard Letter)] Prerequisite(s): ANLY 6100 - Prerequisite Min. Grade: C- Equivalent Course(s): ANLY 4110 Prerequisite: ANLY 6100

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ANLY 6200: Data Processing and Visualization

3.00 Credits

Southern Utah University

This course introduces methods and tools for data processing, database management, and data visualization used in modern business analytics. Students will learn relational database concepts and SQL for retrieving and preparing data, apply Tableau for building effective visualizations, and explore principles of visual design and data storytelling. The course emphasizes the development of metrics and KPIs, integrating AI tools to enhance KPI ideation and visualization design. By the end of the course, students will be able to design, query, and visualize data in a way that supports strategic decision-making and communicates analytical insights clearly. (Fall) [Graded Letter] Registration Restriction(s): MSBA, MBA, or MAcc majors only or instructor permission

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ANLY 6250: Data Management and Organization

3.00 Credits

Southern Utah University

This course introduces the management and organization of data with an emphasis on modern database tools used in business analytics. Students will gain hands-on experience designing and querying relational and columnar databases using Structured Query Language (SQL). Topics include data modeling, database design, cloud databases, analytic functions, and data movement techniques. Students will also explore how data strategy, governance, and architecture enable organizations to extract value from their data assets. The course incorporates appropriate use of artificial intelligence (AI) tools to assist in evaluating and generating SQL code, optimizing database design, and supporting data strategy and governance planning. By the end of the course, students will be able to design, query, and manage databases; prepare and visualize data for analysis; and develop data strategies that align with business goals. (Fall) [Graded Letter]

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ANLY 6300: Marketing Analytics

3.00 Credits

Southern Utah University

This course provides an overview of the most important analytics methods used in marketing decision making. Students are introduced to common marketing models such as probit, multinomial, and structural equation modeling. Well-established marketing research methods are covered, such as survey and experimental design, along with more recent marketing research tools such as sentiment mining and social-network analysis. (As Needed) [Graded (Standard Letter)] Prerequisite(s): ANLY 6100 - Prerequisite Min. Grade: C Prerequisite Can Be Concurrent? Yes Registration Restriction(s): MSBA majors only or instructor permission Prerequisite: ANLY 6100

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ANLY 6350: Advanced Data Management and Organization

3.00 Credits

Southern Utah University

This course explores the research and application of advanced database and cloud-based data systems with a focus on enabling artificial intelligence and advanced analytics at scale. Students will learn to design and manage AI-ready architectures that support scalable storage, intelligent pipelines, semantic data layers, and real-time inference. Emphasis is placed on leveraging cloud-native tools and AI-augmented development practices to automate data processing, streamline model integration, and ensure secure and ethical data use. ANLY 6350 is a continuation of ANLY 6250, building on foundational concepts to advance students' technical and strategic understanding of data systems. Upon completion, students will be able to evaluate modern data technologies, describe and implement AI-enabled architecture concepts, and apply advanced design principles to build or enhance enterprise data systems. The course also prepares students to deploy intelligent data pipelines, assess AI-optimized technologies, and design governed, explainable strategies for data consumption across analytics and machine learning environments. (Fall - 1st Session) [Graded Letter] Prerequisite(s): ANLY 6250 - Prerequisite Min. Grade: C Registration Restriction(s): MSBA students only Prerequisite: ANLY 6250

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ANLY 6400: Big Data for Business

3.00 Credits

Southern Utah University

This course introduces the theory of an "Internet of Things (IoT)" and how to deal with the massive amounts of data generated by the connections of the IoT. The course includes an introduction to the open-source technologies commonly used to deal with unstructured big data problems, such as Hadoop, Spark, Pig, Hive, and Amazon Web Services. Along with familiarizing students with big data techniques and tools, the course presents real-world business applications and gives students hands-on experience with obtaining valuable information from big datasets. (Spring) [Graded (Standard Letter)] Prerequisite(s): ANLY 6100 and ANLY 6200 - Prerequisite Min. Grade: C Registration Restriction(s): MSBA majors only or instructor permission Prerequisite: ANLY 6100 A ANLY 6200

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