Alteryx Analytics Cloud Product Ideas

We at Grupo Boticário, who currently have 13k Dataprep licenses and close to the official launch internally, have noticed a recurring request for a translation of the tool. Bearing in mind that it will be an enabler for more users to use in their day-to-day work, I would like to formalize and reinforce the importance of our request for translation into Brazilian Portuguese as well as a forecast of this improvement.

Current NIST/NSA standard is SHA-2.

As a data wrangler, I would like to be able to hash a column's data using the SHA-256 hashing algorithm.

We can migrate flows from one environment to other environment using Trifacta APIs.

Export and Import the flow from source to target.

Rename the flow.

Share flow with appropriate user according to environment.

Change the input and output of the flow.

Currently, If there is use-case that the data needs to brought from tables resting in different databases of a same cluster. We have to create n connections for n databases.

But being in same cluster, one should be able to access different databases with a single connection otherwise the connection list gets long and messy.

At the moment the only edit history visible to Trifacta users is within each recipe. Some actions are done within flows rather than recipes, e.g. recipe creation/deletion/taking union/etc. Such actions are not covered within the edit history, but for compliance purposes/troubleshooting it is important for users to know when these actions were taken/who by. Please would it be possible to add the functionality to Trifacta to have an edit history on flows as well as within recipes?

Users onboarded to Trifacta cannot be deleted from the GUI, only using API. In the GUI users can only be disabled but they still count toward the licensed users. Please allow users to be deleted from the GUI.

Users to be able to create multiple connections to data lake. Currently user needs to add new data lake path and browse it in order to import data

In our organization we would like to export path to data lake to be enforced and thus user not able to export to any location but a location desired by the application admins.

When output a Trifacta formated date, like a derived year (year(mydate) ) or formatted to mmddyyyy that when it is published to a SQL table that it maintains that format or transformation. Currently putting out a formatted or transformed date is put out to the SQL Table in the input format and all transformation and formatting is lost.

When creating a destination to and SQL table on an SQL server, allow you to set the field length and not use the Trifacta output standard of varchar (1024). This would help keep the maintenance on the table easier.

I would like the ability to specify a billing project for BigQuery as part of run options. Currently, data queried from BigQuery is associated to the project from which a Dataprep flow is run with no way to change it. For customers we work with in a multi-project environment, they need the flexibility to align queries to specific projects for purposes of cost and usage attribution.

Additionally, for customers on flat-rate BigQuery pricing, a selectable billing project will allow users to move queries to projects under different reservations for workload balancing and/or performance tuning.

In a large enterprise, one of the perennial challenges is to manage changes to data over time.    The industry is moving towards a shift-left philosophy to handle this by starting to think about data contracts and contract testing.

What does this mean for Alteryx?

Well - if you look at the strategy that DBT is following, each workflow has a defined entry data contract, and a defined exit data contract - so that if anything changes you can immediately tell if you are going to break someone else's work.    This also sets you up for lineage in an important way - if you build in field and data-set level lineage from day zero - then you can look across an enterprise and answer questions like:

- If I remove this field - who will I impact downstream (e.g. other Alteryx users; Tableau dashboards etc)

- Who is using my data - so that I can talk to them about their data needs?    Who do I need to tell if my workflow fails

- has someone upstream of me changed their flow in a way that breaks me?

- Where does this field come from - looking across a series of flows and transformations (critical for regulatory requirements).

This kind of thinking is hard to add in afterwards - so it would be good to build this into the product in these early days so that this becomes a key foundational piece.

Hello all,

Sometimes, you find some messy worklow and you want to make it clean

You can align manually the tools but it would be better to have the exact same function than on Alteryx Designer on-premise :

Best regards,

Simon

Hey all,

There is already an option to clean up data in the results section - but it's limited to only the cleanups that the Cleanse tool used to do in the on-prem version.

Please could you use an inspection of the field to see what cleanup may be relevant?

For example:

A_B - there's no need to offer to clean up numbers - or perhaps just visually decrease that option

    A_B - here the obvious cleanup is leading spaces

"A_B" - the obvious cleanup here is remove quotes

It seems that we can bring some smarts to this, since Alteryx AIDAN is AI enabled, to eliminate the toil of data cleansing.

When I rename a field in Alteryx - it would be valuable for Alteryx to look at all tools downstream from the select tool and say "Hey - you are using that field - do you want me to clean up the formulas etc".

A field is not just letters in a formula - a field is a logical concept / an object - so it should be relatively easy to inspect everywhere there's a dependance on this object downstream and just clean this up automatically.

This would get rid of all the painful toil of having to reconfigure tools, change formulae, change select tools etc - that can just all go away in a puff of Aidan Magic.

Hi all,

I'm working through cloud quest 1 using the Alteryx Cloud Native experience - and it seems that there's an opportunity here to get rid of the need to know historical ways of working.

The example in this case is that there are 2 dates:

- 16-Jun-01

- 25-Dec-01

Now it seems that most people used either a RegEx or a DateTimeParse (which still uses the same specifiers since Alteryx 11 - https://help.alteryx.com/current/en/designer/functions/datetime-functions.html#idp376621).   Additionally there doesn't seem to be a DateTimeParse tool in the platform yet in the CloudNative version.

However - given that we're living in the future now - it seems that it should be trivial to use a little AI to recognize that '16-Jun-01' is a date - and allow the user a right-click option to convert to a date.

Please can you consider doing a simpler method of cleaning up dates than forcing the user to remember the classic alteryx specifiers for dates since this is SUCH a common need

Using Challenge 438 as an example, the crosstab in designer cloud needs to be dynamic for the new column names to ensure parity with desktop. Unless I'm missing something, you would need to click on the crosstab and manually reset it/add new fields anytime the data changes. Desktop would automatically pick up new fields.

When people ask what's so great about designer desktop, one of the simple things I mention is the record count. I think this would be a great addition to designer cloud. As an example, here's a pointless workflow in designer cloud:

Seems ok, but here's the same thing in desktop:

By just looking at the picture, you can see that I messed up my join and my 780 records have ballooned to 608,400. I can also see that I didn't have any unjoined records pretty easily. Designer cloud has this record count information when you click on each tool, but I think they should display the counts on the canvas like desktop. 

Replace, ReplaceFirst, ReplaceChar and Regex_Replace in the cloud all have a limitation where arguments must be constants. Any attempt to use a column returns an error. This would a nice enhancement to have parity with Desktop. The below functions currently error out in cloud but work in desktop.

Replace(Column1,Column2, Column3)

Regex_Replace(Column1,Column2,Column3)

Could doesn't like that Column2 and Column3 are references to fields. It only works if you hardcode a string like "text". Desktop doesn't have this limitation.