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Long time viewer, first time poster.
I have a table of facts. There are ~60 columns with ~30,000 rows. The table tracks process parameters. Each row in the table represents a single event.
I would like to be able to have the report consumer select which column is used on the y-axis and the which is used on the x-axis.
There are about 3 columns that act as identifiers (event ID key, facility, date). The remainder are the data that is collected about the event.
The goal is a user-defined linear regression between any two non-identifier columns that exist in the table.
Ive tried using field parameters, unpivoting the table and cross joining to get all possible combinations (this was unworkable), using a copy of the fact table to get the x and y, calculated tables and using a slicer as the way to add columns, etc.
All the usual patterns that work for measures do not work for calculated tables when I tried.
Any ideas?
Thanks for the reply Amit. I partially solved the problem. Field parameters were the solution.
Sample Data:
Set up two identical Field Parameter tables, one for the x-axis and one for the y-axis:
Created Scatterplot visual and put the "columns" in the x and y-axis fields of the visual.
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Only thing left is to set up the regression. But I cannot refer to the data that underlies the field parameter columns. I need to create measures for the regression calculations {e.g. SUMX(X-Axis, X-Axis[X-Axis]), SUMX(X-Axis, X-Axis[X-Axis] ^ 2), etc.} but the relevant columns of the field parameter tables are strings. Is there any to access the data that the field parameter is referring to? I tried adding these parameter fields to an add-in visual that performs regression calculations and it works so there is a way to access the underlying data set to perform the calculations. I can't use the add-in because I don't have a license and the dataset is limited to 1000 points in the free version.
Any suggestions?
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