• DATA 1100: Excel for Business Analysis

  1.00 Credits

  Utah State University

  
  This course addresses the importance of Microsoft Excel for business students and guides students toward Excel proficiency for business analytics and certification. It is recommended that students intending to take DATA 2100 take DATA 1100 and DATA 2100 concurrently.
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• DATA 2100: Data and Information in Business

  3.00 Credits

  Utah State University

  
  In this course students tackle real-world problems by using a hands-on approach to develop and apply foundational skills in critical data-centric technologies, including Excel, SQL, and Python programming. Prerequisite/Restriction: DATA 1100 (may be taken concurrently)
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• DATA 3100: Making Decisions with Data

  3.00 Credits

  Utah State University

  
  This course builds on DATA 2100 to help students understand how to draw conclusions or inferences from data. Topics include probability, sampling distributions, and basic inference for averages and proportions, including t-tests, ANOVA, chi-square tests, and simple regression models. Prerequisites/Restrictions: DATA 2100 with a grade of C or better One of the following: ACT Math score of at least 25 or equivalent SAT Math score MATH 1050 or MATH 1100 with a grade of C- or better ALEKS PPL Math Placement Exam score of at least 55
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• DATA 3300: Introduction to Modern Data Analytics

  3.00 Credits

  Utah State University

  
  This course provides an introduction to advanced business intelligence and analytics, using modern analytics tools and strategies to build exploratory and predictive models, and applying evidence-based methods to inform business decisions and actions. Prerequisites/Restrictions: One of the following: ?DATA 3100 with a grade of C or better STAT 1040 STAT 1045 STAT 2000 STAT 2300 STAT 3000
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  General Education Course

  This course is a general education course.

• DATA 3330: Database Management

  3.00 Credits

  Utah State University

  
  This course teaches the theory and application of designing, developing, and maintaining database systems. Students learn principles of management of data resources to support effective information systems in organizations.
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• DATA 3400: Data Visualization with Tableau

  3.00 Credits

  Utah State University

  
  This course familiarizes students with the fundamental principles of data visualization, emphasizing the identification of appropriate data visualization techniques and the development of visualizations using the Tableau software package.
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• DATA 3500: Introduction to Python Programming

  3.00 Credits

  Utah State University

  
  This course provides an introduction to programming basics using Python with an emphasis on tools for data analytics, including input/output of large datasets, data extraction from the web, and basic prediction and decision making.
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• DATA 4330: Advanced Database and Database Analytics

  3.00 Credits

  Utah State University

  
  This course covers advanced database topics such as concurrency control, XML databases, and web-based databases. A heavy advanced SQL and analytics focus is also a part of the course. Prerequisite/Restriction: DATA 3330
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• DATA 5330: Data Pipeline Engineering

  3.00 Credits

  Utah State University

  
  This course explores the design and engineering of effectively structured data ecosystems. Using programming tools, students develop efficient and effective dataflows to ensure quality data are available to meet critical data analysis requirements. Additional coursework is required for those enrolled in the graduate-level course. Prerequisite/Restriction: DATA 3330 DATA 3500 Dual Listed: DATA 6330
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• DATA 5360: Data Warehousing Data Warehousing

  3.00 Credits

  Utah State University

  
  This course introduces the process of creating and populating data warehouses for enterprise-level decision making. Topics include data consolidation from operational SQL databases via ETL process, database schema design and implementation, and various report generation. Additional coursework is required for those enrolled in the graduate-level course. Prerequisite/Restriction: DATA 3330 Dual Listed: DATA 6360
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