Alteryx Designer Desktop Ideas

I have a process that sends out about 1,500 emails. Every once in a while, it will get stuck at some Percentage and I will have to eventually cancel the workflow, figure out how many emails were sent, and then skip that many emails in order to avoid sending duplicate emails. The process of figuring out how many were sent is currently taking the % of the tool at cancellation minus 50%(since that is where it starts), Multiplying it by 2, and then multiplying that % by the number of lines to get the approximate line of data where it froze up, and then reaching out to individuals to see if they received the email to narrow down exactly where the error occurred. 

Example: 60% - 50%= 10% * 2 = 20% * 1249 = 249.8.

This has been pretty accurate in the past, but obviously is not ideal. Is there no way for it to show us how many were sent even if we cancelled the workflow mid processing of the tool?

The older versions of the Publish to Tableau Server Macro had an option to Request an authentication token however the latest version does not.  Please return this option to the tool as it is very useful for constructing Rest API call scripts.

Thank you!

~ Eric Marowitz

Please allow a hover over that would show you the value of a variable in the formula tool. At times I get long formulas and it would be nice to see the values of each variable by just putting your mouse on top of it. Just show the first row like the preview. There is similar functionality in visual studio and it makes coding easier. 

To compare a Grid shape before a change and after the change, both shapes should have a reference point where those grids can be created.

The reference point should be changed according to the coordinates system that the designer want to use

Sort by file size based on first digit in file size (should be based on all digits). 

Please provide an option to have a the caption of a tool container sent to log/results after all items within it have been processed.

When using the Transpose tool I'm pivoting out networks names to column headings then I want to populate those fields with an "X".  To do this I have to first create a column first with an "X" in it and populated the various Networks columns with that.

How about another drop-down that says something like "I'll key the value I want to populate the fields with" and I can key "X" or "Y", etc.

It's possible I just don't know enough about the tool but I can't see how to do this other than my way.

When working on the Weekly Challenge #108, I was trying to design a non-macro solution.

I ended up settling on the Generate Rows tool and was trying to find a way to generate rows until I had reached or exceeded the maximum density, however, I ran into an issue where I'd always have one too few rows, since the final row I was looking for was the one that broke the condition I specified.

In order to get around this, I came up with the following solution:

Spoiler

 

Essentially, I just set my condition to twice that of the true threshold I was looking for. This worked because I was always doubling the current value in my Loop Expression, and so anything which broke the 'actual' condition I was looking for ([MaxDensity]), would necessarily also break the second condition if doubled again.

However, for many other loop expressions, this sort of solution would not work.

My idea is to include a checkbox which, when selected, would also generate the final row which broke the specified condition.

By adding such a checkbox, it would allow users to continue using the Generate Rows tool as they already do, but reduce the amount of condition engineering that users are required to do in order to get that one extra row they're looking for, and reduce the number of  potentially unseen errors in their workflows.

The CrossValidation tool in Alteryx requires that if a union of models is passed in, then all models to be compared must be induced on the same set of predictors. Why is that necessary -- isn't it only comparing prediction performance for the plots, but doing predictions separately? Tool runs fine when I remove that requirement. Theoretically, model performance can be compared using nested cross-validation to choose a set of predictors in a deeper level, and then to assess the model in an upper level. So I don't immediately see an argument for enforcing this requirement.

This is the code in question:

if (!areIdentical(mvars1, mvars2)){
        errorMsg <- paste("Models", modelNames[i] , "and", modelNames[i + 1],
                          "were created using different predictor variables.")
        stopMsg <- "Please ensure all models were created using the same predictors."
      }

As an aside, why does the CV tool still require Logistic Regression v1.0 instead of v1.1?

And please please please can we get the Model Comparison tool built in to Alteryx, and upgraded to accept v1.1 logistic regression and other things that don't pass `the.formula`. Essential for teaching predictive analytics using Alteryx.