| Course | AC444 Accounting Visualization and Business Intelligence |
|---|---|
| Unit | Unit 4 |
| Paper type | Data model exercise |
| Length | About 570 words, 5 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | BS in Accounting |
| Updated | October 2026 |
Free sample paper for AC444 Unit 4
Two Fact Tables, Five Dimensions, Eight Measures: A Unit 4 Star Schema for a Pest Control Company
[Student Name]
Purdue University Global
AC444: Accounting Visualization and Business Intelligence
Unit 4 Data Model Exercise
[Instructor Name]
[Date]
Ashgrove Pest Control and every figure are composite; the books cited are real.
Fact Tables
FACT_SERVICE_VISIT. Grain: one row per completed service visit. About 84,600 rows for 2025. Keys: date_key, branch_key, service_line_key, customer_key, technician_key. Facts: billed_amount, labor_minutes, labor_cost, materials_cost.
FACT_ACCOUNT_MONTH. Grain: one row per recurring account per month-end. A periodic snapshot of about 168,000 rows for 2025. Keys: date_key, branch_key, service_line_key, customer_key. Facts: status_flag (1 if active), canceled_flag (1 if canceled during the month).
Visits and account status get separate fact tables because they have different grains: a visit happens at a moment, while an account's status is a condition at month-end, and forcing both into one table would either repeat status on every visit or invent visits for months with none.
Dimensions
1. DIM_DATE: date_key, date, month, quarter, year, season flag (April to October mosquito season). Shared by both facts.
2. DIM_BRANCH: branch_key, branch name, region, technician capacity hours per month. Shared by both.
3. DIM_SERVICE_LINE: service_line_key, line name (residential, commercial, termite, mosquito), recurring flag. Shared by both.
4. DIM_CUSTOMER: customer_key, customer type, start date, ZIP code. Joined to both.
5. DIM_TECHNICIAN: technician_key, name, branch, hire date. Joined to visits only.
Shared dimensions are what let a view filter visits and account status by the same branch and month (Kimball & Ross, 2013).
Measures, Defined in Writing
1. Revenue: sum of billed_amount.
2. Direct labor: sum of labor_cost.
3. Materials: sum of materials_cost.
4. Gross margin: revenue minus direct labor minus materials.
5. Margin percent: gross margin divided by revenue, computed after summing, never averaged across rows.
6. Route hours: sum of labor_minutes divided by 60.
7. Active accounts: sum of status_flag at the selected month-end. Semi-additive: it may be summed across branches and service lines at one month-end, but never across months. Over a quarter, use the last month's value.
8. Churn rate: sum of canceled_flag in the period divided by active accounts at the start of the period.
Two Design Notes
Customers who move between branches are handled by keeping the branch on each fact row rather than only on the customer, so a visit counts where it happened. The customer dimension keeps history: when a residential customer converts to a commercial contract, a new dimension row is added with its own effective date, so last year's figures do not change after the fact. That technique, a type 2 slowly changing dimension, keeps reports reproducible (Kimball & Ross, 2013). Interactive views built on a model like this let accountants explore data at different levels, which research on visualization in accounting systems identifies as their main benefit (Dilla et al., 2010).
Why Definitions Come First
Writing each measure before building a view prevents the most common errors in business intelligence work: summing a balance across time, averaging percentages instead of recomputing them, and two analysts producing different numbers for the same label (Few, 2013). The active accounts measure is the trap here. Summed across the twelve month-ends of 2025, it would report about 170,000 accounts for a company that has 13,980.
Checks Planned
Revenue in FACT_SERVICE_VISIT will be reconciled to the general ledger, and active accounts at December 31 to the customer subledger, before any view is published (Kimball & Ross, 2013).
References
Dilla, W., Janvrin, D. J., & Raschke, R. (2010). Interactive data visualization: New directions for accounting information systems research. Journal of Information Systems, 24(2), 1-37. https://doi.org/10.2308/jis.2010.24.2.1
Few, S. (2013). Information dashboard design: Displaying data for at-a-glance monitoring (2nd ed.). Analytics Press.
Kimball, R., & Ross, M. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling (3rd ed.). Wiley.
What the AC444 Unit 4 assignment asks for
Unit 4 of AC444 asks you to design the data model a set of views will draw on. Identify each business process to be measured and state its grain in one sentence, such as one row per completed visit. Use separate fact tables where grains differ, for example events versus month-end snapshots. List the dimensions, note which are shared across facts and give each its key and main attributes. Define every measure in plain language and as a formula, stating how it aggregates. Flag semi-additive measures, which can be summed along some dimensions but not across time, and say how they should be totaled over a period. Address design issues such as dimension history. State the reconciliations you will perform before publishing views. Cite a dimensional modeling source and visualization or accounting systems research in APA 7.
Inside the AC444 Unit 4 example
The sample specifies FACT_SERVICE_VISIT at one row per completed visit and FACT_ACCOUNT_MONTH as a month-end snapshot, each with keys and facts. The highlighted sentence explains why different grains require two fact tables. Five dimensions follow, with a note that shared dimensions let views filter both facts together, citing Kimball and Ross. Eight measures are defined, from revenue to churn rate, with margin percent recomputed after summing and active accounts flagged as semi-additive. Two design notes cover branch placement on fact rows and type 2 history for customers who change type, citing Dilla and colleagues on interactive views. A section explains why definitions come first, showing that summing active accounts across months would report about 170,000. Planned reconciliations to the ledger and subledger close the exercise.
Where the points sit in the AC444 Unit 4 rubric
AC444 data model exercises are graded on correct grain, appropriate fact table design and precise measure definitions. Each fact table's grain should be stated in one sentence, and graders check that facts with different grains are not forced together. Dimensions should be shared where views need to filter several facts at once. Each measure needs a definition precise enough to leave no room for two answers, and ratio measures must be recomputed after aggregation rather than averaged. Identifying semi-additive measures and stating how to total them over time is a key criterion, because it prevents the most common dashboard error. Handling history in dimensions shows maturity. Planning reconciliations links the model to reliable reporting. A readable diagram and APA 7 citations to the modeling literature earn what remains of the Purdue Global grade.
Common AC444 Unit 4 mistakes, and how to avoid them
Many Unit 4 models put visits and account status in one table, repeating status on every visit or inventing rows for months without visits. Grain is never stated, so nobody knows what one row means. Margin percent is stored on each row and averaged. Active accounts is summed across months. Dimensions are duplicated for each fact instead of shared. Customer changes overwrite history, so last year's reports change. If your dataset covers sales orders, payroll or hospital encounters, our writers can define the grain, the facts and the measures for it.
Get an AC444 Unit 4 example written to your instructions
Share the source tables or extract your Unit 4 exercise supplies, the rubric and whichever BI product the course requires, since measure syntax varies between products. The schema, grain statements and measure definitions come back within 24-48h, all drawn from your own columns, and a first custom sample costs nothing. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
More AC444 papers and BS in Accounting samples
- AC444 Unit 1: Misleading Chart Discussion Post
- AC444 Unit 2: Investor Chart Critique
- AC444 Unit 3: Single View Build
- AC444 Unit 5: Trend Visualization
- AC444 Unit 6: Comparison View Set
- AC444 Unit 7: Dashboard Build
- AC444 Unit 8: Seminar Reflection
- AC444 Unit 9: Reconciliation Worksheet
- AC444 Unit 10: Executive Briefing Deck
- AC442 Unit 4: Normalized Table Design
- AC430 Unit 4: Earnings and Profits Schedule
- AC420 Unit 4: FIFO Process Costing Worksheet
- AC410 Unit 4: Internal Control Walkthrough
AC444 Unit 4 questions, answered
What does semi-additive mean in practice?
A measure that can be summed along some dimensions but not others. Active accounts can be added across the six branches at one month-end to get a company total, but adding January through December produces a number that describes nothing. The sample defines the measure to take the last month-end value in any period, and the definition states that rule in words.
Why two fact tables instead of one?
Because the two sets of facts have different grains. Visits happen at a moment; account status is a condition at month-end. Forcing both into one table either repeats account rows for every visit or loses accounts with no visits that month. Separate facts sharing conformed dimensions keep both correct and still let a view show them side by side.
Does the exercise require a specific tool?
Sections differ. Some want the model built in a BI application with relationships and measures defined there, while others accept a diagram and written specification. The sample provides both, and measure formulas can be written in the expression language of whichever tool your section uses once you name it.
Where can I find a free AC444 Unit 4 sample paper?
This page holds a complete AC444 Unit 4 data model exercise for a composite pest control company, with two fact tables, five dimensions, eight defined measures, design notes and APA 7 references.
What happens if active accounts is summed across months in AC444 Unit 4?
It counts each account once per month. Over the twelve month-ends of 2025 it would report about 170,000 accounts for a company that has 13,980, so a quarter or year uses the last month's value.