Alteryx Designer Ideas

This idea arose recently when working specifically with the Association Analysis tool, but I have a feeling that other predictive tools could benefit as well.  I was trying to run an association analysis for a large number of variables, but when I was investigating the output using the new interactive tools, I was presented with something similar to this:

 

 

While the correlation plot draws your high to high associations, the user is unable to read the field names, and the tooltip only provides the correlation value rather than the fields with the value.  As such, I shifted my attention to the report output, which looked like this:

 

 

While I could now read everything, it made pulling out the insights much more difficult.  Wanting the best of both worlds, I decided to extract the correlation table from the R output and drop it into Tableau for a filterable, interactive version of the correlation matrix.  This turned out to be much easier said than done.  Because the R output comes in report form, I tried to use the report extract macros mentioned in this thread to pull out the actual values.  This was an issue due to the report formatting, so instead I cracked open the macro to extract the data directly from the R output.  To make a long story shorter, this ended up being problematic due to report formats, batch macro pathing, and an unidentifiable bug.  

 

In the end, it would be great if there was a “Data” output for reports from certain predictive tools that would benefit from further analysis. While the reports and interactive outputs are great for ingesting small model outputs, at times there is a need to extract the data itself for further analysis/visualization.  This is one example, as is the model coefficients from regression analyses that I have used in the past.  I know Dr. Dan created a model coefficients macro for the case of regression, but I have to imagine that there are other cases where the data is desired along with the report/interactive output.

 

Hi,

 

I wasted a good old chunk of time dealing with non-breaking spaces, and Alteryx could be improved by handling this automatically.

 

A space is a space, right?  Nope, there are spaces (ASCII value decimal 32) and there are non-breaking spaces (ASCII value decimal 160).  They look the same, but have slightly different behaviour in certain circumstances, like when text is auto-wrapped.

 

The DataCleansing tool cleans spaces, but leaves non-breaking spaces.

The Data Grid puts a warning on cells with leading or trailing spaces, but remains silent for non-breaking spaces.

 

I was trying to match two strings, that looked identical.  I had DataCleansed my cells, and the grid was showing me nothing wrong with the data.  In desperation, I copied the two data cells that I expected to match to a text editor (Textpad), and then examined the binary ASCII values of the data.  One cell had a trailing non-breaking space, and that caused the failure to match.

 

This was hard to find.  For someone less hopelessly nerdy, it would be practically impossible. 

 

As a small change, it might be really useful for Alteryx to include non-breaking spaces in it's definition of "space", such that DataCleansing tool removes it, and the Data Grid flags up the cell as having a leading or trailing space.

 

You could pick up non-breaking spaces from HTML, or from Excel.  I think mine came from a SQL script but I am not sure how it was there.  They are out there, and they will bite.

Python pandas dataframes and data types (numpy arrays, lists, dictionaries, etc.) are much more robust in general than their counterparts in R, and they play together much easier as well. Moreover, there are only a handful of packages that do everything a data scientist would need, including graphing, such as SciKit Learn, Pandas, Numpy, and Seaborn. After utliizing R, Python, and Alteryx, I'm still a big proponent of integrating with the Python language much like Alteryx has integrated with R. At the very least, I propose to create the ability to create custom code such as a Python tool. 

Hi,

 

I wasted a good old chunk of time dealing with non-breaking spaces, and Alteryx could be improved by handling this automatically.

 

A space is a space, right?  Nope, there are spaces (ASCII value decimal 32) and there are non-breaking spaces (ASCII value decimal 160).  They look the same, but have slightly different behaviour in certain circumstances, like when text is auto-wrapped.

 

The DataCleansing tool cleans spaces, but leaves non-breaking spaces.

The Data Grid puts a warning on cells with leading or trailing spaces, but remains silent for non-breaking spaces.

 

I was trying to match two strings, that looked identical.  I had DataCleansed my cells, and the grid was showing me nothing wrong with the data.  In desperation, I copied the two data cells that I expected to match to a text editor (Textpad), and then examined the binary ASCII values of the data.  One cell had a trailing non-breaking space, and that caused the failure to match.

 

This was hard to find.  For someone less hopelessly nerdy, it would be practically impossible. 

 

As a small change, it might be really useful for Alteryx to include non-breaking spaces in it's definition of "space", such that DataCleansing tool removes it, and the Data Grid flags up the cell as having a leading or trailing space.

 

You could pick up non-breaking spaces from HTML, or from Excel.  I think mine came from a SQL script but I am not sure how it was there.  They are out there, and they will bite.

Python pandas dataframes and data types (numpy arrays, lists, dictionaries, etc.) are much more robust in general than their counterparts in R, and they play together much easier as well. Moreover, there are only a handful of packages that do everything a data scientist would need, including graphing, such as SciKit Learn, Pandas, Numpy, and Seaborn. After utliizing R, Python, and Alteryx, I'm still a big proponent of integrating with the Python language much like Alteryx has integrated with R. At the very least, I propose to create the ability to create custom code such as a Python tool. 

One of the tools that I use the most is the SELECT tool because I normally get large data sets with fields that I won't be using for a specific analysis or with fields that need re-naming. In the same way, sometimes Alteryx will mark a field in a different type than the one I need (e.g. date field as string). That's when the SELECT comes in handy.

 

However, often times when dealing with multiple sources and having many SELECT tools on your canvas can make the workflow look a little "crowded". Not to mention adding extra tools that will need later explanation when presenting/sharing your canvas with others. That is why my suggestion is to give the CONNECTION tool "more power" by offering some of the functionality found in the SELECT tool.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

For instance, if one of the most used features of the SELECT tool is to choose the fields that will move through the workflow, then may be we can make that feature available in the CONNECTION tool. Similarly, if one of the most used features (by Alteryx users) is to re-name fields or change the field type, then may be we can make that available in the CONNECTION tool as well.

 

 

At the end, developers can benefit from speeding up workflow development processes and end-users will benefit by having cleaner workflows presented to them, which always help to get the message across.

 

 

What do you guys think? Any of you feel the same? Leave your comments below.

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

A question has been coming up from several users at my workplace about allowing a column description to display in the Visual Query Builder instead of or along with the column name. 

 

The column names in our database are based on an older naming convention, and sometimes the names aren't that easy to understand. We do see that (if a column does have a column description in metadata) it shows when hovering over the particular column; however, the consensus is that we'd like to reverse this and have the column description displayed with the column name shown on hover. 

 

It would be a huge increase to efficiency and workflow development if this could be implemented.

One of the tools that I use the most is the SELECT tool because I normally get large data sets with fields that I won't be using for a specific analysis or with fields that need re-naming. In the same way, sometimes Alteryx will mark a field in a different type than the one I need (e.g. date field as string). That's when the SELECT comes in handy.

 

However, often times when dealing with multiple sources and having many SELECT tools on your canvas can make the workflow look a little "crowded". Not to mention adding extra tools that will need later explanation when presenting/sharing your canvas with others. That is why my suggestion is to give the CONNECTION tool "more power" by offering some of the functionality found in the SELECT tool.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

For instance, if one of the most used features of the SELECT tool is to choose the fields that will move through the workflow, then may be we can make that feature available in the CONNECTION tool. Similarly, if one of the most used features (by Alteryx users) is to re-name fields or change the field type, then may be we can make that available in the CONNECTION tool as well.

 

 

At the end, developers can benefit from speeding up workflow development processes and end-users will benefit by having cleaner workflows presented to them, which always help to get the message across.

 

 

What do you guys think? Any of you feel the same? Leave your comments below.

Hi All,

Not sure if there is already tool like this, if not, it would help to have a test data generator.

It would be a combination of data type and nature of data. For e.g. Person Name whose meaning is self explanatory and is a string. Similarly phone number which is numeric but would be different than sales amount.
This can help save time during the development and QA phases when real live data might not be available and team would need to mock up such data for testing the code developed.

It may be driven by either some sort public databases like Government provides portals/APIs or internal alteryx maintained dictionary data.

An advanced step to this might be data generated by purpose. Say even inside Person name data would be different when testing a plain use caae vs master data management use case.

It would be great to have a way to find a column by its name.

This feature would be particularly useful when exploring with data sets having a large number of fields.

This feature would be useful within several tool, in particular with the "Browse" tool and with the "Input" tool.

Ideally the user should be able to  "Ctrl-F" and jump to the column matching the name being typed.

Alternatively, the user could be able to sort the columns alphabetically.

 

Thank you for considering this feature suggestion.

 

Davide Gerbaudo

 

P.S. I understand from this discussion that such feature is not currently available.

Right now there is not an exception join in DB which means if I want to remove records I have to filter on NULL and with large tables this is really inefficient.

Hi All,

Not sure if there is already tool like this, if not, it would help to have a test data generator.

It would be a combination of data type and nature of data. For e.g. Person Name whose meaning is self explanatory and is a string. Similarly phone number which is numeric but would be different than sales amount.
This can help save time during the development and QA phases when real live data might not be available and team would need to mock up such data for testing the code developed.

It may be driven by either some sort public databases like Government provides portals/APIs or internal alteryx maintained dictionary data.

An advanced step to this might be data generated by purpose. Say even inside Person name data would be different when testing a plain use caae vs master data management use case.

In addition to the existing functionality, it would be good if the below functionality can also be provided.

 

1) Pattern Analysis

 

This will help profile the data in a better way, help confirm data to a standard/particular pattern, help identify outliers and take necessary corrective action.

 

Sample would be - for emails translating 'abc@gmail.com' to 'nnn@nnnn.nnn', so the outliers might be something were '@' or '.' are not present.
Other example might be phone numbers, 12345-678910 getting translated to 99999-999999, 123-456-78910 getting translated to 999-999-99999, (123)-(456):78910 getting translated to (999)-(999):99999 etc.

 

It would also help to have the Pattern Frequency Distribution alongside.

So from the above example we can see that there are 3 different patterns in which phone numbers exist and hence it might call for relevant standadization rules.

2) More granular control of profiling

 

It would be good, that, in the tool, if the profiling options (like Unique, Histogram, Percentile25 etc) can be selected differently across fields.

 

A sub-idea here might also be to check data against external third party data providers for e.g. USPS Zip validation etc, but it would be meaningful only for selected address fields, hence if there is a granular control to select type of profiling across individual fields it will make sense.

 

Note - When implementing the granular control, would also need to figure out how to put the final report in a more user friendly format as it might not conform to a standard table like definition.

 

3) Uniqueness

 

With on-going importance of identifying duplicates for the purpose of analytic results to be valid, some more uniqueness profiling can be added.

 

For example - Soundex, which is based on how similar/different two things sound.
Distance, which is based on how much traversal is needed to change one value to another, etc.

 

So along side of having Unique counts, we can also have counts if the uniqueness was to factor in Soundex, Distance and other related algorithms.

 

For example if the First Name field is having the following data -

 

Jerry
Jery
Nick
Greg
Gregg

 

The number of Unique records would be 5, where as the number of soundex unique might be only 3 and would open more data exploration opportunities to see if indeed - Jerry/Jery, Greg/Gregg are really the same person/customer etc.

 

4) Custom Rule Conformance

 

I think it would also be good if some functionality similar to multi-row formula can be provided, where we can check conformance to some custom business rules.

 

For e.g. it might be more helpful to check how many Age Units (Days/Months/Year) are blank/null where in related Age Number(1,10,50) etc are populated, rather than having vanila count of null and not null for individual (but related) columns.

 

Thanks,

Rohit

Hi All,

I think this suggestion would be be ideal for the Join tool and it's related cousins (Join Multiple etc.) and would improve the experience of data blending for all users.

I am going to rely on Qlik Sense for this explanation as this functionality is native to that product.

 

When we bring in two data sources and use the join tool to blend we are required to select the field or fields upon which we want to base our join.

In Qlik Sense we can see our two data sources:

 

 

We can then drag them together and it will form suggestions based on data association density:

 

 

This helps with identifying how tables should be joined, and at the very least shows commonalities between data streams, based on the data within the tables and not any naming conventions.

It would be nice to have the functionality to generate suggestions based on association density between two data streams, and then to apply the join from a selection.

 

 Thoughts?

It would be great to have a way to find a column by its name.

This feature would be particularly useful when exploring with data sets having a large number of fields.

This feature would be useful within several tool, in particular with the "Browse" tool and with the "Input" tool.

Ideally the user should be able to  "Ctrl-F" and jump to the column matching the name being typed.

Alternatively, the user could be able to sort the columns alphabetically.

 

Thank you for considering this feature suggestion.

 

Davide Gerbaudo

 

P.S. I understand from this discussion that such feature is not currently available.

Hi,

 

Seems there is inconsistency across tool when it comes to being case sensitive.

 

One simple example might be - For Join it works based on case sensitivity, but for Formula (Multi Row) - it works based on case insensitivity.

 

The Idea is to make the functionality case sensitive for all tools.

 

Benefits -

 

1) When some code is written in Alteryx, it works same way when coming to case consistency, and does not differ tool-by-tool.

2) It is common practice to make use of functions (Uppercase/Lowercase) to ignore differences coming out of case sensitivity for items like joining with some standardized values (like List of Values etc), so it should not be much of an overhead. At times the case related differences might be something which needs to be treated differently.

3) If a tool ignores case sensitivity, there might not be an easy way (if not - no way available) to make it work for case sensitivity as per business requirement, but vice versa is attainable making use of Uppercase/Lowercase case conversion functions.

 

Thanks,

Rohit Bajaj

When working with large amount of data the browse tool profiling causes the program to stop responding.

 

A feature to disable the profiling per browse tool.

or even better

After a set threshold (e.g. amount of rows), the auto profiling is disabled and requires an action to run.

When working with large amount of data the browse tool profiling causes the program to stop responding.

 

A feature to disable the profiling per browse tool.

or even better

After a set threshold (e.g. amount of rows), the auto profiling is disabled and requires an action to run.