CSV to Power BI, from any system's export
Updated by CompileBI
A CSV from your CRM, your ticketing tool, your finance system or a survey platform is enough. CompileBI reads the delimiter and the types, treats the file as one table, plans the report and returns a .pbip project you open in Power BI Desktop.
Dates are read as dates when the file stores them that way. A date written as text, such as 12/03/2026 in a text column, stays text, and the report will say that no time axis was available rather than guess a day and a month.
Upload a fileHow it works
- 01
Upload the file
Drop an .xlsx of up to 50 MB, or a .csv of up to about 18 MB, into the chat. Every sheet is read: its columns, types, dates, blanks and keys. Add a one-line note if you like, such as who the report is for and what it should help decide.
- 02
The report is planned and built
The engine decides which questions the data can answer, writes a DAX measure for each figure, evaluates every measure two ways and refuses any that disagree, then lays out the pages so nothing overlaps. Two to four minutes on a typical workbook.
- 03
Open it in Power BI Desktop
Where the report comes with a Power BI file (.pbit), download it and double-click it: Power BI Desktop on Windows opens it and loads the data as it opens, and saving it keeps it as a .pbix. Every report also comes as a .pbip project in a .zip, to unzip into a short folder and open the same way. It is your file: edit any visual, add pages, publish it wherever you publish reports.
What you get
- A summary page and drill pages, with date, category and reset controls
- A DAX measure for every figure, checked two ways before the file is handed over
- A .pbip project validated against Microsoft's report schema
- A list of what the report answers and what the data could not support
- Up to ten changes by chat on paid plans, each producing a new version
Questions
How large can the CSV be?
About 18 MB for most files; an Excel workbook can be up to 50 MB. The limit is really the amount of data, so a CSV with many columns or very many rows reaches it sooner. A CSV past it is refused when you attach it, with the reason stated, not partly read. Remove columns you do not need, or split it, for example by year.
Can I combine several CSV files?
Not yet. One file becomes one report. A workbook with several sheets is read as several tables, so combining exports into one .xlsx first is the way to get one report from them.
Will the measures be correct?
Each measure is written in DAX and evaluated two ways, in Python and in the model, and the report is refused if the two disagree. NPS and CSAT use their defined formulas, not a plain average.