Syllabus
Accounting Systems and Analytics
Course Overview
| Course Number | ACCTG 320 |
|---|---|
| Course Name | Accounting Systems and Analytics |
| Quarter | Autumn 2026 |
| Meeting — Section A | Monday, Wednesday · 13:30–15:20 · PACCAR 292 |
Why study accounting analytics?
Accounting information is central to decision making across the organization. Accounting information systems maintain and store accounting information for analysis. Analysis can be performed on data extracted from accounting systems using accounting analytics. Accounting analytics is a set of techniques that accounting professionals can use to gain insight from their own firms’, their clients’, and other data to make better decisions. The focus of this course is on understanding and applying the use of accounting data to answer important business questions. Students will learn how to apply the analytical mindset by drawing conclusions, making decisions, and communicating insight from accounting data. Accounting data is used practically in this course by developing a practical analytic skillset that provides students with the skillset to design, perform, interpret, and communicate insight from raw accounting data using modern analytic tools.
I am excited to undertake our accounting analytics journey together!
Asher
How this course fits into the Accounting options:
Accounting Systems and Analytics (ACCTG 320) is a required course in the accounting option. The course provides foundational business knowledge in accounting that provides concrete examples of how accounting data is used to make decisions in multiple different settings. The settings examined in ACCTG 320 relate to foundational accounting questions of managerial accountants, external users of accounting information, auditors, and regulators.
The accounting department recommends taking ACCTG 320 early in the program. Like ACCTG 301, this course is introductory in nature with subsequent courses in the accounting option providing a greater depth of understanding of accounting concepts: the financial reporting concepts in ACCTG 302 and 303, financial statement analysis in ACCTG 440, auditing concepts in ACCTG 411, and tax planning concepts in ACCTG 321. The class also introduces at a high-level the analytical mindset, analytical skillset and future-proofing skills that are currently taught in the Master of Professional Accounting program.
Learning Objectives
- Prepare accounting data for analysis. Identify data-quality issues. Apply appropriate ETL transformations. Validate transformed data against source records.
- Use analytics to investigate accounting questions. Develop appropriate analytical questions. Interpret results using accounting context and professional judgment.
Faculty Info
Grading Policies and Assignments
| Assignment | Format(s) | Weight |
|---|---|---|
| Professionalism | Software, Written Assignment | 10% |
| Individual Case Submissions | 15% | |
| Mid-Term Exam 1 | 15% | |
| Mid-Term Exam 2 | 30% | |
| Data Visualization Challenge | 30% |
Professionalism
An individual assessment of student professionalism throughout the quarter. Students are expected to maintain a professional approach to work and approach all classes as professional engagements.
- Submit the completed analytical workflow.
- Submit a short memo describing the transformations and validation performed.
Course Calendar
| Session | Date | Topic |
|---|---|---|
| 1 | Introduction to the Analytics Mindset and Skillset | |
| 2 | Data Quality | |
| 3 | Extract, Transform, and Load (ETL) Fundamentals | |
| 4 | ETL: Combining and Summarizing Data | |
| 5 | ETL: Cleaning and Transforming Data | |
| 6 | Transaction Analytics: Understanding Transactions | |
| 7 | Transaction Analytics: Identifying Unusual Activity | |
| 8 | Mid-term Exam 1 | |
| 9 | Integrating Analytical Skills 1 | |
| 10 | Integrating Analytical Skills 1 | |
| 11 | Financial Statement Analysis | |
| 12 | Analyzing Accounting Disclosures | |
| — | Veterans DayNo class | |
| 13 | Generative AI and Accounting Information | |
| 14 | Mid-term Exam 2 | |
| 15 | Data-Driven Decision Making | |
| — | Thanksgiving BreakNo class | |
| 16 | Introduction to Data Visualization | |
| 17 | Effective and Misleading Visualizations | |
| 18 | Data Visualization Workshop | |
| 19 | Data Visualization Challenge |
Course Policies
Foster Integrity Principles
I will uphold the fundamental standards of honesty, respect, and integrity and I accept the responsibility to encourage others to adhere to these standards.
HONESTY: I will be truthful with myself and others.
RESPECT: I will show consideration for others and their ideas and work.
INTEGRITY: I will be a leader of character. I will be fair in all relations with others.
Access and Accommodations
Your experience in this class is important to me. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course. If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or uwdrs@uw.edu or disability.uw.edu. DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.
Religious Accommodations
Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW's policy, including more information about how to request an accommodation, is available at The UW's policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.
AI
In all Foster courses, use of generative AI tools is permitted without disclosure as a learning and productivity tool, except on specific assignments or assessments where it may be prohibited, restricted, or required to ensure you build the foundational knowledge and skills your career will depend on. You are responsible for the accuracy, integrity, and originality of all individual and team submitted work. AI-generated content should be augmented with your substantial human judgment to meet the desired standards or learning objectives, and you should be able to explain and defend anything you submit to your instructor or teammates. See the Foster AI Syllabus Statement for full details and responsibilities. Use of AI in violation of assignment-specific guidelines constitutes academic misconduct under the UW Student Conduct Code (Academic Misconduct Policy).