| Course | BU 451 Programming for Business Analytics |
|---|---|
| Unit | Unit 7 |
| Paper type | Error handling and validation |
| Length | About 710 words, 5 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | BS in Business Analytics |
| Updated | September 2026 |
Free sample paper for BU 451 Unit 7
Seven Guards, Seven Bad Inputs, Seven Clear Refusals: Error Handling and Validation for a Composite Paddle Rental Company's Analysis Pipeline
Student Name
Business, Herzing University
BU 451: Programming for Business Analytics
Instructor Name
April 8, 2026
Seven Guards, Seven Bad Inputs, Seven Clear Refusals: Error Handling and Validation for a Composite Paddle Rental Company's Analysis Pipeline
What the Pipeline Depends On
So far the Riverbend scripts, written for the composite paddle outfitter in this course, work on the files they were given. They also depend on assumptions about those files that nobody has checked since: that the export is complete, that prices can be read as numbers, that only three site codes exist, that every date falls in the season, that each lookup table has one row per key, and that joins and totals reconcile. When the owners send the 2026 data, any of those assumptions could fail, and a script that keeps running on broken data produces confident-looking wrong answers. This unit adds guards at the points where each assumption could first be wrong, makes each guard stop with a message naming the failed assumption, and proves each one works by feeding it something that should not pass.
Validation, in the sense used here, is the explicit statement of rules data must satisfy, checked every time the data change, rather than an inspection done once by eye (van der Loo & de Jonge, 2018). Wilson et al. (2014) recommend that programs check their own operation with assertions, statements that stop the program when a condition the programmer believes true turns out to be false.
Where Each Guard Sits
Each guard is placed at the earliest point its assumption could fail, so an error is caught near its cause rather than several steps later.
| Guard | Placed after | Assumption checked | On failure |
|---|---|---|---|
| 1. Row count in range | Loading rentals | The export is complete: 15,000 to 25,000 rows | Stop |
| 2. Required columns present | Loading each file | All columns later code uses exist | Stop |
| 3. Prices are numbers in range | Price conversion | Every price converts; none below $0 or above $400 | Stop |
| 4. Site codes known | Site code fix | Only CHA-1, CHA-2, CHA-3 appear | Stop |
| 5. Dates in season | Date parsing | All dates between April 1 and October 31 of the season year | Stop |
| 6. Lookup keys unique | Before each join | One row per date in weather, per site in sites and fleet | Stop |
| 7. Totals reconcile | After each join and before output | Row counts unchanged; rental and revenue totals match | Stop |
| Record-level issues | Cleaning | Missing return times, impossible durations | Flag and continue |
Stop or Recover
The pipeline makes a deliberate distinction. Structural problems, those that make the whole file or a whole column untrustworthy, stop the run. A truncated export, an unreadable price or an unknown site code means something happened upstream that a person must look at, and continuing would spread the error through every table. Record-level problems that the cleaning rules already handle, such as a missing return time, are flagged and counted, and the run continues, since the rules for them were decided in the cleaning unit and the rest of each record is valid.
Every stop uses the same form of message: what was checked, what was found and what to look at. A message such as "KeyError: 'price'" tells a reader where the program failed but not why; the guards replace errors like that with messages written for the person who will fix the data, who may be the owner rather than a programmer. The message should let that person act without opening the code: which file, which rows, which values, and what the script expected instead.
Each Guard Shown Failing
Each guard was demonstrated with a copy of the data altered to break its assumption, kept in a test folder so the demonstrations can be rerun.
| Guard | Bad input fed to it | Message the script printed |
|---|---|---|
| 1 | Rentals file cut off after 900 rows | Stopped: rentals file has 900 rows; expected 15,000 to 25,000. Check that the export finished. |
| 2 | Column renamed from price to amount | Stopped: rentals file is missing required column 'price'. |
| 3 | One price entered as $4O, letter O for zero | Stopped: 1 price could not be read as a number (row 5,211, value '$4O'). |
| 4 | Twelve rentals coded CHA-4 | Stopped: unknown site code CHA-4 in 12 rows. Known sites: CHA-1, CHA-2, CHA-3. |
| 5 | Three rentals dated October 2024 | Stopped: 3 rentals dated outside the season, which runs April 1 to October 31, 2025. |
| 6 | Weather file with September 14 listed twice | Stopped: weather has 2 rows for 2025-09-14; one row per date is required. |
| 7 | A join altered to use the wrong key | Stopped: row count changed from 642 to 1,284 after joining sites. |
Each demonstration also confirmed the guard's position, and each altered file is kept so the demonstrations can be repeated whenever a guard is edited. The letter O in a price, for instance, is caught immediately after conversion, not at the revenue total three scripts later, where it would have appeared only as a revenue figure slightly lower than it should be. And the duplicated weather date that the aggregation unit found by accident is now caught on purpose, before any join runs.
How Many Guards Are Enough
Seven guards is not a target, and more would not automatically be better, since every guard is code that must itself be maintained. The test used to decide whether an assumption deserved a guard was whether its failure would produce a wrong answer silently. A missing column fails loudly anyway, with an error, but the guard is kept because its message is clearer. A duplicate lookup key fails silently by multiplying rows, which is why it has a guard before every join. Assumptions whose failure would be obvious in the outputs, such as a figure with no data in it, were not given separate guards. McKinney (2022) notes that most errors in data work come not from the code's logic but from data that differ from what the code expected, and the guards are placed where the data first meet the code's expectations. Riverbend Paddle Co. and all of its files and test cases are composites for this course.
References
McKinney, W. (2022). Python for data analysis: Data wrangling with pandas, NumPy, and Jupyter (3rd ed.). O'Reilly Media.
van der Loo, M., & de Jonge, E. (2018). Statistical data cleaning with applications in R. Wiley.
Wilson, G., Aruliah, D. A., Brown, C. T., Chue Hong, N. P., Davis, M., Guy, R. T., Haddock, S. H. D., Huff, K. D., Mitchell, I. M., Plumbley, M. D., Waugh, B., White, E. P., & Wilson, P. (2014). Best practices for scientific computing. PLOS Biology, 12(1), Article e1001745. https://doi.org/10.1371/journal.pbio.1001745
Reading the BU 451 Unit 7 instructions
The seventh unit of BU 451 asks students to add validation and error handling to their code. Common requirements are identifying the assumptions the code depends on, checking each at the point where it could first fail, stopping with informative messages, deciding when to stop and when to continue, and demonstrating each check with input designed to fail it. Many instructors ask how many checks are enough and whether a script should recover or stop. Messages should help the person who must fix the data, not only the programmer. The submission usually includes the revised code, a set of test inputs and an APA 7 explanation with a table of guards and their demonstrations.
Inside the BU 451 Unit 7 example
The paper begins by listing the assumptions the existing scripts rely on and the risk of confident wrong answers. A table places seven guards with the assumption each checks and the action on failure. A section sets the rule for stopping versus flagging and describes the standard form of every stop message. A second table shows each guard fed a specific bad input and the exact message it printed. A paragraph notes that each guard catches its problem close to the cause. The final section explains the test used to decide which assumptions deserve guards and why the duplicate-key guard sits before every join.
BU 451 Unit 7 rubric: what full points look like
Validation rubrics at Herzing usually reward identification of assumptions, well-placed checks, informative messages, a clear stop-or-continue policy and demonstrations of each check, plus writing and sources. Assumption identification earns credit when checks follow from what the code actually needs. Placement scores highest when each guard sits at the earliest point its assumption can fail. Messages are judged on whether they name what was checked, what was found and what to do. The policy criterion rewards a stated rule tied to earlier cleaning decisions. Demonstrations earn full points when every guard is shown failing on purpose, since an untested check proves nothing. A saved folder of the bad test inputs also helps, because it lets the demonstrations be repeated after any later change to the guards.
Common BU 451 Unit 7 mistakes, and how to avoid them
Validation exercises often lose points by adding checks that are never shown failing. Another common problem is placing all checks at the end of the pipeline, where an error is far from its cause. Students frequently write messages such as error in data that help nobody. Some stop the run for every small record issue, making the pipeline unusable, while others let structural failures pass with a warning. Many forget to check key uniqueness before joins, the source of silent row multiplication. Finally, writing checks against a pipeline you support at work may expose system details; demonstrating the same guards on course data avoids that.
Get a BU 451 Unit 7 example written to your instructions
Share the instructions and rubric for this BU 451 unit, plus the script you want protected and the data it runs on. The custom example places its guards at the read, the reshape and the write, stops rather than warns, names the assumption in every message and proves each check with a broken copy. First custom sample free, 24 to 48 hours.
More BU 451 papers and business analytics samples
- BU 451 Unit 1: Environment and setup exercise
- BU 451 Unit 2: Data import and inspection script
- BU 451 Unit 3: Cleaning and transformation in code
- BU 451 Unit 4: Control flow and functions
- BU 451 Unit 5: Aggregation and joins
- BU 451 Unit 6: Analysis script with output
- BU 451 Unit 8: Reproducible analysis submission
- BU 407 Unit 7: Simulation output brief
- BU 351 Unit 7: Reporting to a business audience
- BU 453 Unit 7: Integrity and transactions
- BU 454 Unit 7: Dashboard with hierarchy
BU 451 Unit 7 questions, answered
How many checks are enough?
Count the assumptions the script actually makes and write one guard for each. If the code relies on a column existing, on an identifier being unique and on a date range holding, that is three checks and the file needs three. Anything beyond the assumptions the script depends on is decoration, and a marker reading fifteen guards will assume the writer did not know which mattered.
Should the script recover from a failure or stop?
Stop, unless the instructions describe a case where continuing is meaningful. Recovery makes sense when a single record is unusable and the rest are fine, and even then the count of skipped records has to be reported. Recovery from a structural problem, such as a missing column, means producing output from something the code no longer understands, which is worse than failing.
Can I write these checks against a pipeline I support at work?
Running them there is your job and none of it becomes coursework. Validation rules encode what an employer knows about its own data, and the failures they catch describe systems the company has not opened to a school. Anything pointed at live infrastructure is also work we will not draft on your behalf. The graded version belongs on the unit's file.
Where can I find a free BU 451 Unit 7 sample paper?
The complete BU 451 Unit 7 error handling and validation example is free above, with the guard table, the failure demonstrations and margin notes. For your own pipeline, share the instructions and we will design matching guards for you free, usually inside two days.
Should a BU 451 Unit 7 script recover or stop?
It depends on the problem. The sample stops on structural failures, such as unreadable prices or unknown site codes, and flags record-level issues the cleaning rules already handle, like missing return times.