community
cancel
Showing results for 
Search instead for 
Did you mean: 

Alteryx Promote Ideas

Share your Promote product ideas - we're listening!

1 Review

Our submission guidelines & status definitions before getting started

2 Search

The community for a solution or existing idea before posting

3 Vote

By clicking the star in the top left corner of an idea you support

4 Submit

A new idea to suggest a product enhancement or new feature


Suggest an idea

Please offload map rendering, in Browse Tool, to the video card using DirectX or OpenGL, the software rendering currently used is embarrassingly slow and disruptive.  

Some customers would like to log all inputs & outputs that go into each model. The goal is to save every JSON request and response with minimal (or no) impact to latency. 

One key challenge that we have is promoting regular canvasses (not just advanced analytics models).

 

It would be very useful if Promote could be made part of the core product of the server:

a) split the server into 1;2;3 environments (Dev; UAT; Prod)

b) Promote then manages the workflow to promote an asset between these environments, with a configurable workflow that allows for signoffs; diff checks; control checks (e.g. are people using tools in the right way; DB connection strings etc); and then writing a copy into the firm source-code repository.

c) Promote should also then change the links in canvasses to point to a prod version of the databases and APIs if relevant.

 

This process is currently extremely manual and labour intensive; so if we could apply the same Promote process to regular canvasses it would be a big time saving for our admin teams.

 

cc: @revathi

It would be extremely useful to have an option to paginate over the output of a Promote Alteryx model. 

 

For example, suppose the output of a model is :

 

[
{
"object_id": 1
"class" : 1
},
{
"object_id": 2
"class" : 0
}
...
]

 

 

...if that output contains hundred of thousands of items, it could be important to be able to paginate over that output instead of returning the whole thing at once and risking a timeout.

send application and server logs from a promote instance to Elasticsearch using logstash or fluentd

So there we have a hosted version of Alteryx Server at gallery.alteryx.com

 

Why not to have a "hosted" version for Promote

  • Would be possible to test it
  • See example deployments
  • Deploy basic models from Alteryx Trial to "Promote" trial
  • Even this can generate a new revenue stream (pay as you score)

Picture3.png

 

 

 

0 Stars

Hello Alteryx Community,

 

I've recently started using Alteryx and one option on the Output Data tool I think that could be useful to others and myself is the option to choose: Append to an extract file (Create if does not exist). This is similar to the already existing Overwrite existing extract file (Create if does not exist) option.

 

My case for this is... I'm in the situation where I'm setting up a flow that I know from the offset is going to be a repeatable flow that is designed to build up data over time and so I will be running the Output Data tools in append mode. Except for the first run, I can't append to an extract that doesn't exist! The flow in question has over around 20 Output Data tools and while it wouldn't take terribly long to reconfigure after the initial run, it is a bit tedious. I think there is scope for my proposed option for being implemented either as a standalone option or to replace the current append option.

 

Example of my current flow:

Capture.PNG

0 Stars

At the moment the salesforce connector does not support view objects like AccountUserTerritory2View. It should be extended to support those objects to facilitate more efficient and above all complete data extraction. 

0 Stars

Extend the machine-learning framework for pressure analysis on a single well to multiwell systems.  

The framework should capture the well interference accurately and be able to test a greater area of the reservoir. Develop a machine-learning model to reconstruct the flow-rate history by use of pressure data. Ensure that both models maintain the advantages of the machine-learning- based single-well pressure interpretation in terms of the accuracy of prediction, computational efficiency, and tolerance to noise.