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Alteryx Designer Ideas

Share your Designer product ideas - we're listening!
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Hi to all,

 

I have seen one or two posts requesting ability to total up rows and/or columns of numbers, however this idea also requests the ability to subtotal data by a field and also produce an overall total.

 

This could be an extension to existing tools such as 'Summarise' and 'Cross Tab' or could be a stand alone tool.  Desired output of using a tool like this would produce something like this:

 

totals.JPG

 

This would be incredibly useful for building reports within Alteryx as well as analysing the data, and cut down the amount of tools currently required to produce this.  I have seen a third party tool which does some of this but this adds the ability to subtotal.

 

thanks - Roger

0 Likes

Hi 

1:
I'm from Denmark, and like several other european countries we use commas instead of dot as decimal seperator. And we use dot as thousand seperator.

So if im working in a flow with loads of price fields, lets say cost price, amount per unit, amount and amount including vat i need to do a multi field replace. Else I dont get the output i can work with in excel or other programs.

So it would be great beeing able to set seperators on a flow level, like you can in excel when importing.

2.
Beeing able to set a date format on a flow level.
Lets say my input data is 12.12.2019 and i need 2019-12-12 in my output. If i work with several different date fields i need to use several datetime fields.
Alternate could be a multi field datetime ? 

 

3.
Having a search function when using the select ? And maybe a numbers order.

So if i scroll down, i could enter 3 - which means this would now be my 3. shown field? 

I usually have some checks of my workflows. The simplest are row counts at varying points. I use Count Records tools, rename the outputs using a Select tool, Union them, and use a Message tool to calculate and show Deltas. I want to have the ability to control the output field name of the Count Records tool the same way I can control the output field name of a Record ID tool.

Please add measures of statistical central tendency to the Summarize tool, such as:

Mid-range

Midhinge

Quartile

Thank you.

With the 2019.3 release the summarize tool now includes prefixes for grouped fields. While a nice addition, in application it makes using this data downstream (like joining to other tables) more involved because of needing to remove this prefix. 

 

It would be nice to have this as an option (a checkbox to add/remove prefixes maybe) or just revert back to pre-2019.3 behavior...thanks!

Disabled Containers throw errors if it contains any interface tools. It should not throw any error as the user is intentionally disabling the container.  

 

clipboard_image_0.png

OK, this one will only save a single click per addition of a tool, but with Alteryx's general awesomeness small annoyances become like a stone in the shoe.

 

Consider my highly complex workflow below ; having inspected the dataset I now realise that I don't want some of the fields in my dataset...

 

SwitchToInput_1.PNG

 

...so I drag a Select tool in to deselect the columns, but I can't remember what the dataset looks like and I can't see the data...

 

 

SwitchToInput_2.PNG

 

...so I click on the Input tab and there it is, I can deselect away !

 

SwitchToInput_3.PNG

 

It would be particularly useful with something like a Summarize tool where I like to see the data to decide which aggregation to use.

 

Thanks !

Currently the cross tab tool automatically sorts alphabetically by the "New Column Headers" field. Often times I have to output data with dates across the columns and therefore have to do a cross tab to achieve this. The problem is when I have the dates formatted with month names, the crosstab automatically sorts it in alphabetical order instead of date order (i.e. Apr, Aug, Dec, etc vs Jan, Feb, Mar). To get around this issue, I have to use a dynamic rename tool. It would be great if there was a way to choose the order of the crosstab (i.e. in the order of the data, crosstab, another field, etc.).

  • Category Transform

With the continued growth of Graph Databases, it would be nice for Alteryx to creates a new tool set that would allow input/output connectors for Graph Databases like Neo4j which software tools like Pentaho and Talend already have.

 

Keith. 

I have a process that joins 3 data sets to identify a specific group of data and apply certain ruling. From this created file, I need to extract the data (not the headings) from specific columns and insert into an already existing template. The template has formatting that needs to remain in order for it to function. 

 

Is this possible? 

0 Likes

Would be nice if in Designer customer's may want to upload and reference  a " DATA DICITIONARY - METADATA REPOSITORY file when working with various input source to transform data . 

Organizations that are mature in their data governance strategy implement special software that extracts, manages and provides access to data dictionary of data assets in multiple databases such as  ERWIN to maintain schema for enterprise. 

Within DESIGNER access to a file METADATA REPOSITORY held in DESIGNER customer may easily select a list of columns  fields or attributes from that file to manipulate data elements using DESIGNER and provide all the relevant information required they wish to massage the data.

Possible Attributes that may be in data dictionary file:

Table name

Column Name

Data Type
Foreign Table

Source

Table Description

Sensitive Data

Required Field

Values

  • Category Transform

While In-db tools are very helpful and cut down the time needed to write complex SQL , there are some steps that are faster by directly writing SQL like window functions- OVER (PARTITION BY .....). In Alteryx, we need to create multiple joins and summaries to perform a window function. It would be immensely helpful if there was a SQL editor tool for in-db workflows where we can edit the SQL code at any point in the workflow, or even better, if they can add an "edit" function to every in-db tool where we can customize the SQL code generated and then send to the next tool.

 

This will cut down the time immensely and streamline the workflow to make Alteryx a true contender for the ETL solution space.

0 Likes

Hello Community,

 

 

I was wondering if there is a tool that could de-duplicate records after serializing (or after using Transpose Tool) with a given priority for each field in one of the keys? i.e.

 

ID Origin Field Name Value
1 A NAME JACK
1 B NAME PETER
1 B ZIP CODE 15024
1 C ZIP CODE 15024
1 D TYPE MID
1 H TYPE

PKL

 

Assuming for the field name NAME, the priority should be [ A, B ]

ZIP CODE -> [ C, B ]

TYPE -> [ H, D ]

The expected outcome for Id 1 should be -> JACK, 15024, PKL

Record discarded -> PETER, 15024, MID

In this case I'm using ID and Origin as keys in the Transpose Tool.

 

I just want to make sure there is no other route than the Python Tool.

 

Thank you

 

Luis

  • Category Transform

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?

 

 

Hi, I have searched through the community, and I wasn't able to find a duplicate for this idea. If in fact there is, I apologize and please point me to that post. I think that it would be a good idea to have date options in the summarize tool that would allow for grouping at higher levels of the date. I often have a date field that is specific to the day (i.e. 2018-01-01), and I just want to group by the year or month. Currently in order to do this, I have to create a formula before the summarize tool that formats the date according to how I want to group it, and then I am able to group off that field in the summarize tool. It would be nice if in the summarize tool, I could select the date field, and then have the option to group it at year, month, week, etc. 

  • Category Transform

Please create the ability to Concat a field in the In-DB Summarize Tool similar to the regular Summarize tool. This would enable much faster processing on concatenating fields using the database's processing power vs. the local machine.

Hi,

This feature isn't a must - but would definitely be a nice to have.

Similar to the excel having a tab with key figures like average, count and sum 

It would be a really good idea to do something similar within Alteryx just to have a quick glance on key figures/functions (example attached - apologise for the bad paint job but definitely would look good with Alteryx colour scheme)


Thanks


These tools seem to be volatile, as in if you click on them before you run the workflow they lose their configuration. This is infuriating. Can we change this to be like every other tool where you can copy, paste or click into it at any time and it remembers its config.

 

Nick

  • Category Transform

PLEASE add a count function to Formula/Multi-Row Formula/Multi-Field Formula!

 

I have searched for alternatives but am just confused about how to store the result for the total number of rows from Summarise or Count Records in a variable that can then be used within a Formula tab. It should not be that difficult to just add equivalents to R's nrow() and ncol().

0 Likes

Improve Help Documentation or in-tool options for handling null values in statistical tools like Weighted Average or Linear Regression. For instance, checkbox to remove null value records, or at least warn users.

 

In the processing of learning to perform linear regression in RStudio and Alteryx, I came across differing outputs depending on how null values were addressed. Take the Weighted Average tool for example.

 

In R, the weighted.mean function treats null values in the variable of interest as if they were not there. If the user does not specify that null values exist, the result is NA. If any null values exist in the weight field, the result is NA.

 

Since I am more familiar with Alteryx, I originally did the data preparation—including calculating the weighted means—in Alteryx. When comparing these weighted means with those generated in R, I found that Alteryx treats the null values as zeros (i.e. includes them in the calculation). The user would have to know this is incorrect and first filter out the null values. See screenshot examples.

 

 

 

This is also the case within the Linear Regression tool. If null values are not omitted prior to regression, the results are wildly different. Perhaps this is known by more experienced users/statisticians, but this incorrect usage would have gone on unbeknownst to be had I not cross-checked with RStudio.

 

Alteryx_WeigtedAvg.PNGWeighted Average in AlteryxR_WeightedMean.PNGWeighted Mean in R

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