Southern Utah University

Course Syllabus

Southern Utah University
Southern Utah University
Spring Semester 2026

Advanced Data Management and Organization (Online)

ANLY 6350-B70

Course: ANLY 6350-B70
Credits: 3
Term: Spring Semester 2026
Department: MESA
CRN: 10317

Course Description

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. 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.  (Spring - 2nd Session) [Graded (Standard Letter)] Prerequisite(s): ANLY 6250 - Prerequisite Min Grade: C Registration Restriction(s): Masters of Science in Business Analytics

Required Texts

Supplemental Textbooks (Not Required)
Fundamentals of Data Engineering: Plan and Build Robust Data Systems by Joe Reis & Matt Housley
ISBN: 1098108302

Required Software

https://dbeaver.io/download/ DBMS tool with SQLite database
https://console.cloud.google.com/ Google BigQuery
https://sqlbolt.com/  Practice SQL coding
Text editor of your choice (notepad ++, notepad, even MS word)

Learning Outcomes

1. Utilize modern cloud computing systems architecture for optimal data management
2. Describe and evaluate modern data architecture concepts
3. Apply data architecture design principles to build or modify data systems
4. Evaluate and choose data technologies for an AI enabled enterprise
5. Deploy data engineering technologies and development for efficient movement of data
6. Develop data systems for use with analytics, machine learning, and artificial intelligence
7. Design a data management strategy for proper storage, security, and consumption of data

Course Outline

Module 1: Overview of Cloud computing & architecture for AI-Ready Data Systems
Module 2: Data Architecture concepts
Module 3: Data Architecture Design
Module 4: Evaluating & Choosing AI optimized data technologies
Module 5: Data Engineering with AI augmented development
Module 6: AI and Machine Learning Integration
Module 7: AI Driven Governance, Security, and Ethics

Course Requirements

Course Practice Activities
For each module (7 total) in the course, students will be given the opportunity to complete a relevant course practice activity covering material from that particular module. These activities are ungraded, do not require a submission, and a solution will be provided so students can check their work. The purpose of the activities are to provide further learning before completing the scored assignments.

Course Activities
For each module (7 total) in the course, students will be asked to complete a relevant course activity covering material from that particular module.   These activities will be submitted via Canvas as with the individual assignments, though these activities are designed to be shorter and address a particular task of the module. (For example, developing a piece of SQL using a specific function.)

Individual Homework Assignments
Students will be assigned individual homework assignments or analyses throughout the course. These assignments will include tasks designed to introduce and expand knowledge of data management and organizations.  While it is acceptable to discuss aspects of the homework and solution strategy with others, students' submissions should represent their own work. For instance, it would be acceptable to ask for help if you keep getting an error message in SQL, but it would be unacceptable to take someone else’s SQL script, run it, and report the results. When in doubt, consult the professor.  Assignments should be submitted online by the due date and time, a 20% reduction in points will be given for late work.  No late work will be accepted after a solution is posted.  Students will be allowed to make multiple attempts on assignments.

Quizzes
Each module will have an accompanying quiz to test student knowledge of the material (7 total quizzes across the course).   Quizzes and tests are open note, open book, and even open Google. However, students may not work with others on these quizzes, either students registered for the class or others outside the class.  Copying and pasting questions into AI tools and submitting the generated responses is prohibited.  Quizzes and tests will have a time limit and will be taken with only 1 attempt.

Mid-Term and Final
During Module 4 a course Mid-term will be submitted. The midterm will be a paper describing how the techniques and skills gained in this and the prerequisite course will be applied to build their final project. The final will have a combination of multiple-choice, fill-in-the blank, matching, essay questions, and SQL coding questions. The final will cover all topics of the course. Both the mid-term. and final are open note, open book, and even open Google. However, students may not work with others on these quizzes. Copying and pasting questions into AI tools and submitting the generated responses is prohibited. The final will have a time limit of 90 minutes.

Course Project
Students will form teams or work individually to architect, develop, and deploy a small data warehouse using the discussed methodology and techniques in this and the pre-requisite course.  This project will be developed throughout the course, with a final presentation on why and how the final semantic layer was built.  While emphasis will be placed on technical skills during development of the project, particular emphasis will be placed on coherent and accurate explanation of the project in the form of a presentation to presented to a non-technical audience (like a C-suite or board of directors).

Use of AI Tools:
Responsible use of AI for learning and ideation will be permitted and encouraged in specific assignments where noted by the instructor. Unless explicitly allowed in the instructions, students may not use generative AI tools (e.g., ChatGPT, Bard, Copilot) to complete homework, quizzes, or tests. Copying and pasting questions into AI tools and submitting the generated responses is prohibited. These models may produce incorrect or misleading answers when lacking full course context, and such use undermines the learning process. 

Instructor's policies on late assignments and/or makeup work

Late Policy
If an assignment is late but submitted before the sample answer key is posted, it will be graded but with a 20% penalty. If an assignment is submitted after the answer key is posted, it will receive a zero

Make-Up Work / Extra Credit
Make-up work will be considered, but not guaranteed, on a case-by-case basis.  Email the professor if needed.  Some extra credit may be possible throughout the course at the professor's discretion.

Attendance Policy

As this is an asynchronous online course, your attendance will be measured by your participation and completion of course assignments.
Optional "SQL Saturdays" or Office Hours will be conducted over Zoom

ADA Statement

Students with medical, psychological, learning, or other disabilities desiring academic adjustments, accommodations, or auxiliary aids will need to contact the Disability Resource Center, located in Room 206F of the Sharwan Smith Center or by phone at (435) 865-8042. The Disability Resource Center determines eligibility for and authorizes the provision of services.

If your instructor requires attendance, you may need to seek an ADA accommodation to request an exception to this attendance policy. Please contact the Disability Resource Center to determine what, if any, ADA accommodations are reasonable and appropriate.

Academic Credit

According to the federal definition of a Carnegie credit hour: A credit hour of work is the equivalent of approximately 60 minutes of class time or independent study work. A minimum of 45 hours of work by each student is required for each unit of credit. Credit is earned only when course requirements are met. One (1) credit hour is equivalent to 15 contact hours of lecture, discussion, testing, evaluation, or seminar, as well as 30 hours of student homework. An equivalent amount of work is expected for laboratory work, internships, practica, studio, and other academic work leading to the awarding of credit hours. Credit granted for individual courses, labs, or studio classes ranges from 0.5 to 15 credit hours per semester.

Academic Freedom

SUU is operated for the common good of the greater community it serves. The common good depends upon the free search for truth and its free exposition. Academic Freedom is the right of faculty to study, discuss, investigate, teach, and publish. Academic Freedom is essential to these purposes and applies to both teaching and research.

Academic Freedom in the realm of teaching is fundamental for the protection of the rights of the faculty member and of you, the student, with respect to the free pursuit of learning and discovery. Faculty members possess the right to full freedom in the classroom in discussing their subjects. They may present any controversial material relevant to their courses and their intended learning outcomes, but they shall take care not to introduce into their teaching controversial materials which have no relation to the subject being taught or the intended learning outcomes for the course.

As such, students enrolled in any course at SUU may encounter topics, perspectives, and ideas that are unfamiliar or controversial, with the educational intent of providing a meaningful learning environment that fosters your growth and development. These parameters related to Academic Freedom are included in SUU Policy 6.6.

Academic Misconduct

Scholastic honesty is expected of all students. Dishonesty will not be tolerated and will be prosecuted to the fullest extent (see SUU Policy 6.33). You are expected to have read and understood the current SUU student conduct code (SUU Policy 11.2) regarding student responsibilities and rights, the intellectual property policy (SUU Policy 5.52), information about procedures, and what constitutes acceptable behavior.

Please Note: The use of websites or services that sell essays is a violation of these policies; likewise, the use of websites or services that provide answers to assignments, quizzes, or tests is also a violation of these policies. Regarding the use of Generative Artificial Intelligence (AI), you should check with your individual course instructor.

Emergency Management Statement

In case of an emergency, the University's Emergency Notification System (ENS) will be activated. Students are encouraged to maintain updated contact information using the link on the homepage of the mySUU portal. In addition, students are encouraged to familiarize themselves with the Emergency Response Protocols posted in each classroom. Detailed information about the University's emergency management plan can be found at https://www.suu.edu/emergency.

HEOA Compliance Statement

For a full set of Higher Education Opportunity Act (HEOA) compliance statements, please visit https://www.suu.edu/heoa. The sharing of copyrighted material through peer-to-peer (P2P) file sharing, except as provided under U.S. copyright law, is prohibited by law; additional information can be found at https://my.suu.edu/help/article/1096/heoa-compliance-plan.

You are also expected to comply with policies regarding intellectual property (SUU Policy 5.52) and copyright (SUU Policy 5.54).

Mandatory Reporting

University policy (SUU Policy 5.60) requires instructors to report disclosures received from students that indicate they have been subjected to sexual misconduct/harassment. The University defines sexual harassment consistent with Federal Regulations (34 C.F.R. Part 106, Subpart D) to include quid pro quo, hostile environment harassment, sexual assault, dating violence, domestic violence, and stalking. When students communicate this information to an instructor in-person, by email, or within writing assignments, the instructor will report that to the Title IX Coordinator to ensure students receive support from the Title IX Office. A reporting form is available at https://cm.maxient.com/reportingform.php?SouthernUtahUniv

Non-Discrimination Statement

SUU is committed to fostering an inclusive community of lifelong learners and believes our university's encompassing of different views, beliefs, and identities makes us stronger, more innovative, and better prepared for the global society.

SUU does not discriminate on the basis of race, religion, color, national origin, citizenship, sex (including sex discrimination and sexual harassment), sexual orientation, gender identity, age, ancestry, disability status, pregnancy, pregnancy-related conditions, genetic information, military status, veteran status, or other bases protected by applicable law in employment, treatment, admission, access to educational programs and activities, or other University benefits or services.

SUU strives to cultivate a campus environment that encourages freedom of expression from diverse viewpoints. We encourage all to dialogue within a spirit of respect, civility, and decency.

For additional information on non-discrimination, please see SUU Policy 5.27 and/or visit https://www.suu.edu/nondiscrimination.

Pregnancy

Students who are or become pregnant during this course may receive reasonable modifications to facilitate continued access and participation in the course. Pregnancy and related conditions are broadly defined to include pregnancy, childbirth, termination of pregnancy, lactation, related medical conditions, and recovery. To obtain reasonable modifications, please make a request to title9@suu.edu. To learn more visit: https://www.suu.edu/titleix/pregnancy.html.

Disclaimer Statement

Information contained in this syllabus, other than the grading, late assignments, makeup work, and attendance policies, may be subject to change with advance notice, as deemed appropriate by the instructor.