Instructor: Matthew Gonzales

Email: mgonzales1@lamarpa.edu

Phone: (409)984-6381

Office Hours:

Additional Contact Information:

This course teaches you to answer business questions with data visualization. Using the AMPS model (Ask the Question, Master the Data, Perform the Analysis, Share the Story), you will learn to identify business analytics questions, prepare and evaluate data, build exploratory and explanatory visualizations, and communicate data stories with impact. We emphasize the Gestalt principles of human perception — closure, proximity, similarity, continuity, and enclosure — and how they make visualizations more effective. Hands-on labs are completed primarily in Microsoft Power BI, with additional generative AI (Gen AI) labs in most chapters. The course culminates in a capstone project analyzing U.S. electricity generation data.

• Textbook: Data Visualization: Storytelling with Impact, McGraw Hill, by Richardson, Guymon, and Richardson — with McGraw Hill Connect access. All Connect content must be accessed through Blackboard.
• Software: Microsoft Power BI Desktop (free download from Microsoft).
• Technology: Reliable computer and internet access. Note for Mac users: Power BI Desktop runs only on Windows — there is no Mac version. If you use a Mac, plan to complete labs on a Windows PC (for example, an on-campus computer lab or Windows running in a virtual machine such as Parallels).

Textbook Purchasing Statement: A student attending Lamar State College Port Arthur is not under any obligation to purchase a textbook from the college-affiliated bookstore. The same textbook may also be available from an independent retailer, including an online retailer.

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No prior requires for this class.

Design effective data visualizations to provide new insights into a research question or communicate information to the viewer.

Find and select appropriate data that can be used to create a visualization that answers a particular research question.

Properly document and organize data and visualizations to prepare them for reuse.

Design effective data visualizations to provide new insights into a research question or communicate information to the viewer.

Find and select appropriate data that can be used to create a visualization that answers a particular research question.

Properly document and organize data and visualizations to prepare them for reuse.

Week 1 – Course introduction; the role of data visualization in analytics; overview of tools (Excel, Power BI, Tableau)

Week 2 – Data fundamentals: data types, structured vs. unstructured data, sources, and data quality

Week 3 – Principles of visual perception and design; pre-attentive attributes, color theory, and accessibility

Week 4 – Choosing the right chart: comparison, distribution, composition, and relationship visuals

Week 5 – Data preparation and cleaning; shaping and transforming data for analysis

Week 6 – Introduction to Power BI: importing data, the data model, and building basic reports

Week 7 – Working with measures and calculated fields; aggregations and KPIs

Week 8 – Midterm review and exam; portfolio checkpoint

Week 9 – Interactive dashboards: filters, slicers, drill-downs, and user experience design

Week 10 – Exploratory data analysis: identifying trends, outliers, and patterns visually

Week 11 – Statistical visuals: distributions, correlation, scatter plots, and trend lines

Week 12 – Time-series analysis and forecasting visuals

Week 13 – Geographic and spatial visualization; maps and location-based analytics

Week 14 – Data storytelling: structuring a narrative, audience considerations, and presentation best practices

Week 15 – Ethics in data visualization: misleading visuals, bias, and responsible reporting; final project workshop

Week 16 – Final project presentations and course wrap-up

Midterm Exam – Week 6, due Saturday, October 3 (covers Weeks 1–5)

Capstone Project – Assigned Week 12; due Saturday, November 21 (Week 13). Graded as a test grade; one-time submission, no retakes.

Final Exam – Week 15, due Saturday, December 5 (covers Weeks 7–13)

Final Exam – Week 15, due Saturday, December 5 (covers Weeks 7–13)

A = 90–100

B = 80–89

C = 70–79

D = 60–69

F = 59 and below

Assignments – 30%

Exams – 40% (includes the Midterm Exam, Final Exam, and Capstone Project, which is graded as a test grade)

Quizzes – 30%

Late Work: No late work is accepted for any reason. All graded work for each week closes Saturday at 11:59 PM Central Time. All assignments become available on the first day of class — start early and plan around work schedules, family events, and holidays. Do not wait until Saturday night of the due date to start; technology problems are not an excuse for missing a deadline.

Attempts and Timing: Non-quiz/exam assignments allow 2 attempts and are not timed — this means you may resubmit once before the deadline after catching a mistake. Quizzes, the Midterm Exam, and the Final Exam allow 3 attempts and are timed at 4 minutes per question. The Capstone Project is graded as a test grade and is the only test with a one-time submission — one attempt, no retakes.

Communication: The best way to reach me is through my LSCPA email. I respond within approximately 24 hours on weekdays; messages sent over the weekend will be answered the following business day. Please include your course and section number in your email.

Academic Integrity: All submitted work must be your own. Academic dishonesty — including cheating, plagiarism, and collusion — is governed by LSCPA policy (Faculty Handbook, Section IX, Subsection A). A student found responsible for academic dishonesty will receive a zero on the assignment or exam involved, and a flagrant offense will result in an F for the course, at the instructor's discretion. Student submissions may be checked for plagiarism through Blackboard.

Use of AI Tools: AI tools (ChatGPT, Claude, Copilot, etc.) may be used to help you understand concepts and troubleshoot issues in your own work, and certain labs in this course incorporate generative AI as part of the assignment itself — those labs will say so explicitly in their instructions. Outside of those designated activities, submitting AI-generated work as your own is academic dishonesty, and use of AI on quizzes and exams is prohibited. A good rule of thumb: use AI like a tutor, not like a ghostwriter.

Technology Requirements: This course requires regular access to a computer with a reliable internet connection and the ability to install Power BI Desktop (free from Microsoft). Power BI Desktop runs on Windows only — Mac users should plan to use the campus computer labs, a virtual machine, or Power BI Service in the browser where applicable. Contact me during the first week if this presents a problem.

The AI policy paragraph reflects the Gen AI labs that were part of the DATN build — if you ended up cutting those labs from the final shell, delete the clause about designated activities. Same for the Mac guidance: adjust it if you settled on a different workaround for non-Windows students.

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Be sure to check your campus email and Course Homepage using MyLSCPA campus web portal. You can also access your grades, transcripts, academic advisors, degree progress, and other services through MyLSCPA.

Academic honesty is expected from all students, and dishonesty in any form will not be tolerated. Please consult the LSCPA policies (Academic Dishonesty section in the Student Handbook) for consequences of academic dishonesty.

The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Accessibility Services Coordinator, Room 119, in the Ruby Fuller Building. The phone number is (409) 984-6241.

No food or tobacco products are allowed in the classroom. Only students enrolled in the course are allowed in the classroom, except by special instructor permission. Use of electronic devices is prohibited.

This syllabus is part of LSCPA's efforts to comply with Texas House Bill 2504.

As per Texas law and LSCPA policy, all LSCPA employees, including faculty, are required to report allegations or disclosures of child abuse or neglect to the designated authorities, which may include a local or state law enforcement agency or the Texas Department of Family Protective Services. For more information about mandatory reporting requirements, see LSCPA's Policy and Procedure Manual.

LSCPA is committed to establishing and maintaining an environment that is free from all forms of sex discrimination, including sexual harassment, sexual violence, and other forms of sexual misconduct. All LSCPA employees, including faculty, have the responsibility to report disclosures of sexual misconduct, including sexual harassment, sexual assault (including rape and acquaintance rape), domestic violence, dating violence, relationship violence, or stalking, to LSCPA's Title IX Coordinator, whose role is to coordinate the college's response to sexual misconduct. For more information about Title IX protections, faculty reporting responsibilities, options for confidential reporting, and the resources available for support visit LSCPA's Title IX website.

For more information about the Clery Act and crime reporting, see the Annual Security & Fire Safety Report and the Campus Security website.

If you have a grievance, complaint, or concern about this course that has not been resolved through discussion with the Instructor, please consult the Department Chair.