How to analyse Excel data with AI
To analyse an Excel file with AI: clean the sheet first so it has one header row and one kind of data per column, then upload it, ask specific questions in plain Arabic or English, and ask for the result as a table or chart. Match the totals against your file before you rely on any number.
Good analysis starts with a good question
A file with ten thousand rows says nothing until you ask it something. Before opening any tool, write down the decision you need to make. Do we close the weakest branch? Which product do we stock up on before Ramadan? Which customers are late paying? The decision sets the question, and the question sets the columns you need.
Then comes cleaning, which takes the most time in any analysis. The tool reads the file as it is. If a branch name is typed two different ways, it shows up as two branches. If dates are stored as text, they will not group by month.
After cleaning, analysis is three operations repeated: grouping (sales by branch or month), comparing (this month against last month, this branch against the average) and looking for outliers (an invoice with an unusual amount, a customer who stopped buying). These are the same things pivot tables do in Excel.
The steps
01
Settle the question
Write the decision you need and the three or four questions that serve it.
02
Clean the sheet
One header row at the top, no merged cells, no total rows in the middle of the data, and one column per kind of data.
03
Make values consistent
Branch and product names spelled one way, dates stored as dates, amounts as numbers with no text.
04
Upload the file and describe the columns
Say what each column means, the currency and the period. For example: “The Net column is in Omani rial after discount.”
05
Ask a specific question
“What are the five best-selling products in each branch in the third quarter?” beats “Analyse the file”.
06
Check the result
Match one or two totals directly in Excel. If they agree, the file was read correctly.
07
Turn it into an output
A summary table, a chart, a one-page report or a deck for management, then export it to Excel or PowerPoint.
Which chart for which question?
A trend over time
A line chart: sales month by month.
Comparing categories
Bars: branches or products side by side.
Share of a whole
Bars sorted from largest to smallest, or a pie if there are only a few categories.
A relationship between two numbers
A scatter plot: discount against order size.
One number that matters
Show it large, with the change from the previous period.
Useful questions for any sales file
- What is the monthly sales trend, and the change from the previous month?
- Which products perform best and worst, by quantity and by value?
- Who are the ten biggest customers, and what share of revenue do they make up?
- Which branch or salesperson is above the average and which is below?
- Are there outliers, duplicates or empty cells?
- Which customers bought last year and have not bought this year?
What to check yourself
Three things. First, were all the rows and sheets read? Ask for the row count and compare it with your file. Second, was each column understood the way you mean it? An “Amount” column could be before or after tax. Third, forecasts. Next month's forecast from a past trend is an estimate, not a promise, and it knows nothing about a season or a promotion that has not happened yet.
If the file holds personal data about customers or staff, remove the columns the analysis does not need, such as phone numbers and ID numbers, before you upload it, and follow your organisation's policy on sharing data.
Ready-made prompts
Frequently asked questions
Can it write formulas?
Yes, and it explains what each formula does so you can use it in your own files. Give the column names and positions, and try the formula on a few rows before applying it everywhere.
Which file types can Mibyan analyse?
Excel files and similar tables such as CSV. After the analysis you can create a new sheet and export it to Excel.
Do I need to know pivot tables?
No. You write the question in plain language and get the summary table. Understanding the idea of grouping and comparing does help you ask sharper questions and check the answer.
Why is the result different from my own calculation?
The usual causes: total rows inside the data counted twice, dates stored as text, two spellings of the same name, or another sheet in the file you did not mean. Clean the sheet and ask again, naming the sheet.
Is my data safe when I upload a file?
Upload only what the analysis needs, remove personal columns you do not need, and follow your organisation's policy. How Mibyan handles data is described on the privacy page.