Rows used
Know how many rows actually enter calculations.
Before analysis
Know whether your file can really tell a story .
A clean report starts with a simple question: are the rows used reliable enough to read sales?
In short
The goal is not to fix Excel. The goal is to know what can be read without misleading the decision.
Quick read
What to remember
A short page to know what to check, what to avoid and when to use RGAnalyzer.
Essential fields
Amount, date, customer and product show how far the report can go.
Cautious reading
The report shows limits instead of hiding them.
Simple method
Check before commenting
A few checks often prevent a wrong conclusion about revenue or trend.
Check
- A readable amount to calculate revenue
- A date if you want to read evolution
- Customer and product if you want to prioritize
- A real order number only if you want order-level value
Avoid
- Mixing sales rows, totals and subtotals
- Deleting rows without understanding why
- Forcing a trend when dates are not readable
- Comparing two exports without checking their periods
RGAnalyzer
What RGAnalyzer checks
The report shows what is solid and what should be read carefully.
A simple score shows whether the report can be read confidently.
A preview explains why some rows are not used.
Useful fields are listed clearly: date, amount, customer, product, region, order.
FAQ
Useful questions
Is a file with a few excluded rows unusable?
Not necessarily. The report shows excluded volume and reliability score to keep the reading proportional.
Why check the file before KPIs?
Because a clean KPI depends on the rows and fields that are actually readable.
Can the cleaned CSV be reused?
Yes. The RGAnalyzer cleaned export is designed to be easier to reuse or share.