Audit advanced Works with: Any AI

Power BI Date Table and Time Intelligence Check

Table output Has example

• 📉 Power BI
• 📊 Excel
• 📈 Google Sheets

Check a Power BI model's date table, relationships and year-to-date style measures for gaps and wrong comparisons, with test cases to verify.

The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.

[VERIFY] is an editorial flag, not a blank to fill. Wherever the prompt shows [VERIFY], check that item against a reliable source before you use it.

Please audit how my Power BI model handles dates and time-based measures such as year to date and same period last year. I will paste the structure and the measures. Mark all Power BI and DAX statements [VERIFY].

Inputs: the date table's columns and how it was created [DATE_TABLE_DETAILS], the first and last dates in the date table and in the fact tables [DATE_RANGES], the relationships from facts to dates, including which are active [DATE_RELATIONSHIPS], the time-based measures as text [TIME_MEASURES], and our fiscal year start month [FISCAL_YEAR_START].

Return: (1) a checklist table with columns Check, Result, Evidence, Fix. Include: a single continuous date table, no gaps in dates, covers all fact dates, marked as the date table, relationships on a date column and not on date-time, one active relationship per fact table with inactive ones used on purpose, fiscal columns correct, sorting of month names, and text vs real dates; (2) a review of each time measure: what it calculates in words, risks such as partial periods, the comparison period, and what happens with filters; (3) a test plan with five test cases, each with expected values worked by hand from invented data, for example a month to date value and the previous year comparison, showing the arithmetic; (4) a list of misleading displays, such as comparing a partial month with a full month.

Guardrails: do not write measures I did not ask for; if I ask, label them as drafts to test. Do not guess my data. Work on a copy of the report. Not a replacement for validating numbers with the data owner.

Add a worked example with invented figures: sales through 15 March are 150 and through 31 March last year were 400. Show why a naive comparison misleads and what a fair comparison needs.

Fill in before use

Optional: type your details and the prompt above updates. Nothing is saved or sent.

Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.

Checks (invented)
Date table covers 1 Jan 2021 to 31 Dec 2024. Fact table has sales dated 3 Jan 2025. Result: fails. Rows after 2024 will not appear against a date. Fix: extend the table through the latest planned year.
Relationship: Orders[OrderDateTime] to Date[Date]. Result: warning. Date-time values do not match whole dates, so many rows may drop out. Fix: create a date-only column in the fact table.
Test case: sales 1 to 15 March this year = 150. Last year 1 to 31 March = 400. A naive comparison shows -62.5 percent ((150 - 400) / 400). A fair one compares 1 to 15 March last year, for example 190: (150 - 190) / 190 = -21.1 percent. [VERIFY measure logic in your model]