Yes I may sir but that leads to some incoherencies. Because some time slices last 1 day (case A), some X days inside the month or not (case B), some 1 month (Case C), some X months (case D).

A monthly or daily view implies to transform all: time-slices should last 1 day each (eg. 1 row valid for 1 month is transformed into 30 daily rows and the value is /30). Then when I pivot I get clean results in one shot, that would be ideal.

Currently inside a transformation I fork per case (A, B, C, D) then I regroup all at the end, but I am not satisfied with this approach.

So maybe split each row into a separate dataset using Filter or Slice. Use Sequence to expand all the dates. Stack them all back together and then use Pivot to make a summary.

In the CSV I get there are â€śFrom & Toâ€ť periods like: â€ś2 Jan to 7 Feb, value Xâ€ť or â€ś1 Jan to 31 Jan, value Yâ€ť or value valid for 1 day (and many other combinations). Then Sales department expects to get two reports. One where you see values per day and one where you see values per month.
If you pivot the from dates only it gives incoherent results. What I have to do is â€śto deconstructâ€ť all from/to rows into strict values per day (1 row 1 day 1 value), then make a SUM per day and a SUM per month.

I think Mr Andy (the Admin) gave above the correct way to proceed: Slice, Sequence, Stack, Pivot.