Data Quality Red Flags AI Prompt

Review this dataset for data quality issues that could lead me to wrong conclusions if I do not address them first.

I am not a data engineer — I need you to explain each issue in plain terms and tell me what to do about it.

1. Completeness problems:
   - Which columns are missing data, and how many rows are affected?
   - For each column with significant missing data (more than 5%): could the missing values be a problem, or is it normal for that field to be blank?
   - Is there a pattern to what is missing? (e.g. missing values are concentrated in one region or time period — that is more concerning than random gaps)

2. Accuracy problems:
   - Are there values that look impossible? (negative quantities, prices of $0 on paid products, ages of 150, dates in the future)
   - Are there values that are technically possible but suspiciously unlikely? (every sale is exactly $100, all customer ages are round numbers)
   - Are there columns where the same thing is written in different ways? ('New York', 'new york', 'NY', 'N.Y.' — these are all the same but will be counted separately)

3. Consistency problems:
   - If the same information appears in multiple columns, do they agree with each other?
   - Are there rows where related columns contradict each other? (an order with a delivery date before the order date)

4. Duplicates:
   - Are there exact duplicate rows that should not exist?
   - Are there near-duplicates — the same customer or order appearing twice with slightly different details?

5. What to do:
   For each issue found, tell me:
   - How serious it is: will this issue mislead my analysis (serious) or is it minor (cosmetic)?
   - What I should do before I analyze: fix it, exclude affected rows, note it as a caveat, or ignore it safely
   - How to describe this limitation honestly when I share my findings