| Course | AC570 Data Analytics for Accountants |
|---|---|
| Unit | Unit 3 |
| Paper type | Data preparation log |
| Length | About 570 words, 5 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | MS in Accounting |
| Updated | October 2026 |
Free sample paper for AC570 Unit 3
Coordinated Universal Time and 5,562 False Alarms: A Unit 3 Data Preparation Log for a Tenant Ledger
[Student Name]
Purdue University Global
AC570: Data Analytics for Accountants
Unit 3 Data Preparation Log
[Instructor Name]
[Date]
Stowfield Storage and every figure are composite; the article, textbook and guide cited are real.
Source
Four quarterly exports of the tenant ledger for fiscal 2025, pulled January 14, 2026, totaling 417,620 rows of charges, payments, credits and refunds across 31 facilities. Each export was hashed on receipt so the raw files can be shown to be unchanged.
Exclusion Register
Each exclusion records what was removed, why and how many rows.
E-1, overlap duplicates. The third- and fourth-quarter exports both included September 30. Rows with identical transaction identifiers were removed from the later file: 1,318 rows.
E-2, training facility. Facility 99 is a training environment where staff practice transactions. It is not a real site: 2,406 rows.
After exclusions: 413,896 rows. No other rows were removed. Rows that looked odd, such as negative charges, were kept and flagged for later tests rather than dropped, because unusual rows are often what an analysis is looking for (American Institute of Certified Public Accountants, 2017).
Join Register
Each join records the key, the match rate and what happened to non-matches.
J-1, unit master. Ledger rows joined to the unit master on facility and unit number, to add unit size and street rate. All but 212 rows matched. Of those, 196 came from Facility 14, which renumbered units during a remodel in May; a crosswalk supplied by the facility manager recovered them. Sixteen remain unmatched and are flagged.
J-2, user master. Credit rows joined to the user master on user identifier, to add role and home facility. Every row matched, including 1,229 credits entered by the online portal's system user.
J-3, facility calendar. Rows joined on facility and date to add office hours and time zone. Every row matched.
Transformation Register
T-1, time zone conversion. Timestamps are stored in Coordinated Universal Time. Facilities sit in the Eastern and Central zones and observe daylight saving time. Each timestamp was converted to the facility's local time using its zone from the calendar, with daylight saving applied by date. Read in raw form, 6,921 credits fell outside office hours; after conversion, 1,359 do. The other 5,562 were ordinary afternoon entries that the raw timestamps, four or five hours ahead of local time, pushed into the evening.
T-2, credit type. Free-text reason codes were mapped to five types: promotion, fee waiver, goodwill, correction and other. Mapping rules are listed in an appendix, and 214 credits with blank reasons are typed "other."
T-3, tidy structure. The file was reshaped so that each row is one transaction and each column one variable, which every later test assumes (Wickham, 2014).
Without the time zone conversion, the after-hours test would have reported five times as many exceptions, almost all false, and the real problem, a small number of late manual credits, would have been buried under thousands of ordinary afternoon entries.
Reconciliation to the General Ledger
Prepared credits total $1,548,317. The general ledger's concessions account shows $1,551,267. The $2,950 difference is one manual journal entry on December 31 recording a property-tax pass-through credit outside the tenant ledger; it is documented and explained. Payments and refunds reconcile exactly. The file is tied to the ledger within one explained entry (Richardson et al., 2023).
References
American Institute of Certified Public Accountants. (2017). Guide to audit data analytics. AICPA.
Richardson, V. J., Teeter, R. A., & Terrell, K. L. (2023). Data analytics for accounting (3rd ed.). McGraw Hill.
Wickham, H. (2014). Tidy data. Journal of Statistical Software, 59(10), 1-23. https://doi.org/10.18637/jss.v059.i10
The Purdue Global AC570 Unit 3 instructions
The third AC570 unit asks you to document data preparation so another analyst could repeat it. Describe the source, how it was extracted and how you protected the raw files. Keep an exclusion register listing each set of rows removed, the reason and the count, and explain why unusual rows are kept and flagged rather than deleted. Keep a join register giving each join's key, match rate and treatment of unmatched rows. Keep a transformation register for conversions such as time zones, mapping of free-text codes and reshaping, and show the effect of any transformation that changes results materially. Finish by reconciling the prepared file to an independent total, usually the general ledger, and explain any difference. Reference the AICPA guide, the course analytics text and Wickham (2014) in APA 7.
Inside the AC570 Unit 3 example
The sample's source section notes four quarterly exports hashed on receipt. The exclusion register removes 1,318 rows duplicated on September 30 and 2,406 from a training facility, leaving 413,896, and keeps odd rows flagged. The join register records 212 unmatched unit rows, 196 recovered through a remodel crosswalk, plus full matches to the user master and facility calendar. The transformation register converts timestamps to local time with daylight saving, maps reason codes into five types with 214 blanks as other, and reshapes the file to one transaction per row. The highlighted sentence shows the time zone effect. The reconciliation explains a $2,950 difference as a year-end pass-through entry.
Where the points sit in the AC570 Unit 3 rubric
Preparation logs in AC570 earn points for completeness, counts and a reconciliation. Graders check that every exclusion is counted and justified, that joins report match rates and the fate of unmatched rows, and that transformations are described precisely enough to repeat. The rubric rewards showing how a transformation changes results, as the time zone conversion does, and keeping unusual rows rather than silently dropping them. The reconciliation to an independent total, with any difference explained, is essential evidence that the file is complete. Logs that describe cleaning in general terms, omit counts or skip reconciliation lose substantial credit. Register format and APA 7 references support reviewability.
AC570 Unit 3 help: mistakes that cost points
Weak Unit 3 logs say the data was cleaned without listing what was removed or why. Duplicates are removed without saying how they were identified. Joins are run without checking match rates, so rows disappear unnoticed. Timestamps are used as stored, without checking their zone. Unusual rows, such as negative amounts, are deleted when they may be the very exceptions the analysis seeks. The prepared file is never tied to the general ledger. If your section's dataset differs, a writer can build the three registers and the reconciliation from your extract. A last gap is leaving no record of how free-text reason codes were mapped, which makes every later count by type impossible to check.
Get an AC570 Unit 3 example written to your instructions
Attach the extract from the Unit 3 assignment, or a column list if the file must stay inside your section, along with the brief and the rubric. The log, its registers and a tie-out to whatever control figure your data allows return within 24-48h, each entry repeatable from the raw file. No fee applies to a first custom sample. 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.
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AC570 Unit 3 questions, answered
Does every join need a match rate?
In most AC570 sections, yes. A join is where rows vanish without any error message, so the count of matched and unmatched rows is the only evidence nothing was lost. Here the unit master missed 212 rows; 196 came back through a remodel crosswalk and 16 stayed flagged. If your join matches fully, the log should still record that it did.
What should the log tie out to?
A number produced outside the extract that the prepared file should match, most often a general ledger balance for the same period. The sample ties total credits to the concessions account and explains a 997.37 difference with one late-December entry. If your data offers no ledger figure, a source-system report total or the row count on an extraction receipt can serve, and the log names which one it used.
Where can I find a free AC570 Unit 3 sample paper?
This page holds a full AC570 Unit 3 data preparation log for Stowfield Storage with exclusion, join and transformation registers, a time zone conversion and a ledger reconciliation, with APA 7 references.
Why did the time zone conversion matter so much?
The ledger stores timestamps in Coordinated Universal Time, four or five hours ahead of the facilities. Read raw, ordinary afternoon credits looked like evening entries, inflating after-hours exceptions from 1,359 to 6,921.
Why keep unusual rows instead of deleting them?
Because unusual rows are often what an analysis is looking for. Negative charges or odd amounts are flagged for later tests rather than removed, so the preparation step cannot hide a problem.