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Alteryx Designer Ideas

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After using the Text to Columns tool, I generally find myself using a Select tool to get rid of the original field that I split up. Could an option be added in the config to automatically delete this field once it is split to columns?

  • Parse

I've been dealing with JSON since day one, and to be honest it isn't the best experience I've had.

Converting a hierarchical schema into a tabular one is't a straight forward process, but doing that everyday the old way is time and processing consuming.


What I'm proposing is a tool that can read JSON as input, then display a structural skeleton for the user, or the user can provide such skeleton for the tool, say let's say we have the following input:



{"menu": [{
  "id": "File",
  "popup": {
    "menuitem": [
      {"value": "New", "action": "CreateNewDoc", "icons": ["SAVE", "FLOPPY"]},
      {"value": "Open", "action": "OpenDoc"},
      {"value": "Close", "action": "CloseDoc", "conditions": [11,8,4]}
  "id": "Edit",
  "popup": {
    "menuitem": [
      {"value": "Cut", "action": "TextCut", icons: ["CUT", "SCISSORS"]},
      {"value": "Copy", "action": "OpenDoc"},
      {"value": "Paste", "action": "CloseDoc", "conditions": [5,17]}
"error": false




now to parse this into a table of menuitems we need to use:

  • JSON Parse: convert JSON into one long key:value table
  • TextToColumns: split key into multiple columns
  • Filter: make sure we only get one level from the tree
  • CrossTab: Convert it back into a column based key values.


All of this will give us the most primitive table we can have as:

00CreateNewDoc SAVE,FLOPPYNew
01OpenDoc  Open
02CloseDoc11,8,4 Close
11OpenDoc  Copy
12CloseDoc5,17 Paste


and now if we want to have the parent menu id along side with the menuitems, we will do that again as:

  • Filter: for parent values only
  • CrossTab: for parent values into a table
  • Join: to join Parents with Sub items and add the Parent.Id




Now all of this is done with Concatenating of child items, as cross tab will allow us to only do Concat/First/Last for items with the same grouping values.

And now if we want to process children, count them, or extract their data into another table, we have to add more Filters, more CrossTab and more Joining to get parent IDs for future linking.


So what's I'm proposing?


I'm thinking of a Tool with an interface that give me the ability to choose:

  • Target Branch: which is the main table to be extracted from the branches, in this case it would be menu->popup->menuitem.
  • Parent Values: what values to be appended from parents of the previous table, just like menu->Id and others if exist.
  • Children Data types: selecting the proper and expected data type for children instead of using strings or the existing different columns way.
  • Children Arrays Process: what to do with children branches? either stopping their process and return them as is (Stringify), exclude or do other process like count.


the tool may extract the structure or let the user input such config as the following:



Or Input the Structure as a YAML formatted config or any other way.


This will allow the user to have a quick native tool that does what he wants as it should, and user can use it as much as he want for children and nested values. you just Stringify and repeat and only parse what you need every time.


I hope you consider this for me to replace tens of macros and tools into single tools such so.


Thanks for your help and time and all the best!


  • Parse



It was be nice if we could see the Regex Tool be a little more interactive. I am thinking a little more similar to the Formula tool where you can have expression display. I often use this site first  to practice a Regex formula before applying it. I love how this site highlights the data as you build the expression and also provide a comprehensive quick reference. Just an idea to make it easier for those non Regex experts. 







My problem: I've used the download-tool to download a 40mb XML. Parsing the DonwloadData-field containing this XML results in about 6600 records. The XML-Parse Tool passes the orginal DownloadData field to each record, resulting in quite a bit of memory usage:



XML-Parse Problem.PNG


Suggestion: An option in the XML-parse Tool to not pass the parsed field in its output. 



  • Parse

Was thinking with my peers at work that it might be good to have join module expanded both for desktop and in-database joins.


As for desktop join: left and right join shows only these records that are exclusive to that side of operation. Would it be possible to have also addition of data that is in common?

As for in-db join: db join acts like classic join (left with matching, right with matching data). Would it be possible to get as well only-left, only-right join module?



With the increase number of JSON feeds and the need to properly define the data type for date and date/time fields. It would be useful to have the Auto Field tool detect common date and date/time formats from Strings and assign the Date, Date Time, or Time data type.


Given the following input data:



The select tool confirms is a String



If we use the Auto Field as:


The result is still a String data type (2nd Select Tool)



I would expect this to be Date Time.


One solution would be to create a formula and parse it, but this is not suitable for situations that the field names are unknown.


It would be much easier to have the work done by Auto Field.


I have many monthly financial reports in MS Word that is build up on the same structure (same headings, tables etc.). I would like to import those reports into Alteryx in order to structured and analyse the data in Alteryx and presenting later in Power BI. 


A good solution might be a tool that read the word document and input one row for each paragraph, including some paragraph information like style (e.g. Heading 1, Heading 2, Normal, Punctuation etc.). Where there are tables in the document; several fields should be added and separated in Field 1, Field 2... in order to extract and analyse the content of each table. 


Ref. also the discussion Input Data from Word document (.docx) and the idea Natively Support PDF as Input.

Hi all,

Just to give you some context, we have a customer that requires that for every Tableau workbook we deliver, we must add extra documentation, as for instance, for every calculated field, in which views it's used, and the formula of that field (yes, I know exactly what you're thinking right now :P)

So I decided to take a shortcut and do a workflow that extracts the basic (I mean VERY basic) data from the .twb file, so I can save a lot of time. 


Then I came with this idea...


Having a lot of Tableau's under the hood experts in this Community, It would be great to gather some of them and create a Tableau Documenter Macro.


I'd love tho hear what you think, and who's being able to help.


I'm working on loading some public data available as an .xls doc on the web. I can use the download tool to fetch the file, but then have to save it, and reopen it in a separate input data tool. It would be so much easier if I could just flow the download result into an excel parser tool, but I don't see that as an option unless the download file is XML or CSV.
  • Parse

Currently the only encoding method supported by Alteryx Avro format is deflate.  Please consider improving this to include google snappy approach.


This codec method is referenced in the Avro documentation for supported codex.


It would be good if in the date format option for the Parse tools etc, if there was an option for the 1900 date format used sometimes in Excel/SQL. This is where the date is represented as the number of days from 1/1/1900. If this support was added then the same support for time be represented as a decimal {0,1} would be good as well. Besides this being a nice addition to the software, it would also help with any workarounds stemming from an excel file being open when imported causing the format to come through differently. (Currently if the Excel input file is open in the background which can happen on network available files, the time comes in to Alteryx asa decimal and the date appears as 1900 format).
  • Parse

Very confusing.



- Format sting - %y is 2-digit year, %Y is a 4-digit year.   How about yy or yyyy.   Much easier to remember and consistent with other tools like Excel.



- Format string - 'year' but above function year is referenced as %y ??   Too easy to mix this up.



Also, documentation is limited.  Give a separate page for each function and an overview to discuss date handling.




when parsing XML data, Alteryx does not recognise <![CDATA as being data. This type of XML file is not very common yet is still used today (by me anyway!). Their role is similar to commenting your code in some regards (for those who code).


Could it be possible to add a functionality to alteryx so that we can have it consider the data between these "tags" to be data? 







I would be great to have a json-stat parser. There are probably ways of doing it with the JSON parser but it is appears to be a little bit tricky.
Also, it would be nice to be able to use a json-file as input in a simple manner.
  • Parse

Please extend the DateTime tool to parse ISO 8601 / RFC 3339 type timestamps as well.


These are quite commonly used in APIs nowadays and currently require manual RegEx parsing and DateTime calculations.


So in my line of business we get .txt or .dat files that we consider are dump files with customer data in it. The prior record keeper would then provide their layout that determines where certain participant data lives within those files. So currently we have multiple INPUT DATA tools that all parse for different records using the 'Read it as fixed width text file' radio button in the Resolve File Type window and then 'Use Field Settings from File' that we've created from .flat files.




As you can see above each 'RECORD' has a different field setting within the same file. This is fine when it's a few records but we have some prior record keepers that have 15-40 different records within the same dump file. Because of this, our workflows are being bogged down by having to continually open the same file over and over and apply a different file field setting. So I am suggesting we pull Field settings into a separate tool, sort of like a text to column tool but instead of parsing by a specific delimiter it parses by a specific .flat file that contains Field Settings. so instead of our workflow looking like it does above, it would look something like this:


  • Parse

If Alteryx encounters an error in a RegEx tool - it throws an error:

 RegEx (9) The field "Field1_Matched" is not contained in the record.


This is a somewhat confusing and misleading error message because the input data and the regex configuration have no "Field1" at all, so the error message does not assist with resolving the issue.


Could you please re-look at the error messaging on the RegExt tool to see if we can make RegEx errors easier to resolve by giving a self-descriptive error message?


Example below:

Here I was trying to tokenize by using the . to represent any character - however Alteryx is struggling with this.

Annotation 2019-05-20 223352.png


I suggest to add the functionality to parse date strings containing non-English month/day names into Date format

Maybe by detecting the display language of Windows or the language of the DateTime format in Windows settings.


For example, right now in Alteryx, DateTimeParse('July 2008','%B %Y') works fine, but for French month name, DateTimeParse('Juillet 2008','%B %Y') returns null !

and when calling DateTimeFormat(DateTimeNow(), '%B') we would like to have "Juillet" instead of "July" for French version of Windows/DateTime settings.


Right now, we need to use workaround solutions like SWITCH to solve this issue!




Equipment IdTypeClean Equipment ID
S156Substation 156
123L6Delivery point1236


If I want to create the 'Clean Equipment ID" I would have to use a complicated RegEx expression. Wouldnt it be easier for the end-user to have a function to do so? Like Exclude(string,character)?

In this case it could be: exclude([equipment id],"ABCDEFGHIJKLMNOPQRSTUVWXYZ") and if I wanted just letters it could be exclude([equipment id],"0123456789").


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