To avoid doing the vlookup in excel you can add dimension columns to your dataset. Simply upload one or more "dimension" datasets to 'Mparanza along with your main "fact" dataset.

Just make sure that the key columns in the two files have the same name and that the key column in the dimension file does not have duplicate entries.

Say this is your main csv file


Problem: your "fact" dataset has a "Country" column but you want to analyze by "Continent".

Solution: You prepare a "dimension" file like this, where the "Country" key column has the same name as in your main "fact" dataset.


You can upload more than one "dimension" file. A dimension file can have more than two columns.


Upload your "dimension" files using the "Upload and join dimension tables" upload widget. This widget will appear once you have uploaded your main "fact" csv file.


'Mparanza will automatically left-merge the two "dimension" files to your "fact" file. You can download the joined file to avoid having to join it again in the future.

In terms of "variable dimension" variance analysis output, your waterfall chart will include your new dimensions, but only if these dimensions "explain" the most important change. Columns are never dropped in "fix dimension variance" setting.


In this case "Material", "Product" and "Category" explain the change without need of looking into "Continent" and "Country".


If you want to see the impact of "Continent", add "Continent" to the "choose columns you want to see in every report row" widget and submit again.


The report now includes the "Continent" dimension in every row.


Note that both reports are factually true. The reason 'Mparanza automatically came up with the first and not the second, is because "Steel" (number 1 in the first waterfall) accounts for an increase of 42M, double the increase of "North America" (number 1 in the second waterfall). The % increases are similar (225% vs 288%). Note that if "North America" had shown a (much) higher growth rate than "Steel" it might have come up first even though it is half the size.