Alteryx Designer Desktop Ideas

Why Alteryx does not have an easier way (Drag, Drop, Click and Run) to calculate moving averages with a specified lookback? There are so many things that one has to adjust before calculating moving averages for a simple numeric column.

I understand that there is a CrewMacros called "Moving Summarize" which does that, but it has a limitation of a lookback period of 100. What if you have data with millions of rows where you need a lookback in 1000s then there is no easy solution to this.

Does anyone know that this configuration is in the making? Moving Average is bread and butter for analysts like me. I am urging Alteryx developers to build this tool asap. and it will bring lot of comfort to my troubled soul.

Maybe i am clearly missing something here, please enlighten me!

Thank you!

Is there a way we can turn on and off any tools in the workflow. This way we can run the tool and when a certain tool is marked off it is not executed. This way we can test the workflow and check different output without deleting the tools existing on the workflow, we can just turn then on or off.

When using the transpose and cross tab tools, I find that I frequently need to reorder the columns selected in the "Key Columns" and "Group data by these values" sections of the tools respectively by using a select tool. It would be helpful to provide users with the ability reorder fields displayed in these tools similar to the functionality provided in the select, join, append, summarize tools etc. Currently the tools default to outputting these columns in the order they come in through the incoming data stream. 

Hi currently if you use the cross tab tool and the names of the new fields should have special characters they end up being replaced in the new headers with underscores "_", and then need to be updated in someway. It would be great if this was all done in the tool. In other words the new headers have the special characters as desired

The Summarize tool should have an option to ignore warnings like this:

Group Bys on Double or Float are not recommended due to rounding error.

A problem I'm currently trying to solve and feel like I'm spending way too much time on it..

I have a data set which has some data in it from multiple languages, and I only want English values.  I was able to get rid of the words with non English letters with a little regular expression and filtering.  However, there's some words that do contain all English letters but aren't English.  What I'm trying to do is bring in an English dictionary to compare words and see which rows have non English words according to the dictionary.  However, this is proving to be a bit harder than I thought.  I think I can do it, but it feels like this should be much simpler than it is.

It would be great to have a tool that would run a "spell check" on fields (almost all dictionaries for all languages are available free online).  This could also be useful also just for cleaning up open text types of data where people type stuff in quickly and don't re-read it! 🙂

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. 

Hello, it would be helpful to be able to have multiple levels of detail in a summarize tool. So, rather than aggregating on the lowest level of the group-bys, being able to select the level or partition for the aggregate. The current workaround for this is having multiple summarize tools and joining back to get all the data in one table.

The configuration would look something like this:

With the aggregation field maybe being a pick-list of available "group by" columns. It should default to all the group by columns, but you could un-select some if you wanted a higher level of detail.

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.

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

It would be a handy feature if it were possible to choose a data type for an input tool to read the data in as. For example, if a dataset has multiple fields with different data types, it would be handy to be able to make the Input Tool read and output them all as a string, if needed. This would also make a handy tool, a sort of blanket data conversion to convert all fields to the specified type.

As in title - it might be helpful to define custom name when you are using Transpose tool instead default nomenclature "Name" and "Value".

It would be great if you could select multiple Data Fields in a single Crosstab

For example. I would like to SUM (Methodology) Pet Food Sales (Data Field 1) & Baby Food Sales (Data Field 2) By Store (Grouping Field) By Day of Week (Header field).
 

Looking for a tool to replicate the Goal seek functionality built into Excel.

Seems it could be solved by using R or iterative macros however a tool would make life much easier,

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.

Just like there is search bar for Select Tool, there should be one for Data Cleansing tool also.

Currently both the formula and summarise tools round to 6.d.p for finance calculations such as IRR. People coming from Excel will be used to a higher precision then this. It would be great to up the precision in line with other platforms to 8.d.p +

Hello,

Today I worked with summarize tool and need to merge/concatenate 10 string columns of dataset with different separator than is set up by default (",")

Current status is that you can multiple select columns that you want to concatenate (that's good) but when you want to set up for all output columns different separator than default, you must set up it for each column, in my case it was 10 columns..

one field is selected (Concatenate option is available)

More fields selected (Concatenate option is hidden)

My idea

Allow to multiple selection of fields that are concatenated and allow to set up separator for these fields. Benefit will be that you can mass setup different separator for various fields

I am on a forecasting project where we convert one vector of forecasts into another vector of forecasts by multiplying by a conversion matrix. This is very clumsy and fragile to do in Alteryx meaning we have to drop out to Excel. The ability to do very simple matrix multiplication in Alteryx would be very useful here and in other use cases. I realise you can probably exit to R and do the job, but for something so basic that shouldn't be required.

The relational representation of an mxp matrix is a three column table of cardinality mxp with columns { I , J , A }, where I labels the first index set with index i, J labels the second index set with index j, and A labels the numeric values with value a(i,j).  Given a second pxn  matrix { J, K, B } in relational form we should be able to multiply them to get a mxn matrix { I, K, C} in relational form where of course c(i,k) = sum over j in J of a(i,j)*b(j,k).

Vectors can of course be represented as 1x and x1 matrices. If you really wanted to go to town this could be generalised to array processing ala APL2.